diff --git a/data/ammpdb/ammpdb.biotools.json b/data/ammpdb/ammpdb.biotools.json new file mode 100644 index 0000000000000..b01b6b11bef40 --- /dev/null +++ b/data/ammpdb/ammpdb.biotools.json @@ -0,0 +1,104 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-20T11:34:24.816824Z", + "biotoolsCURIE": "biotools:ammpdb", + "biotoolsID": "ammpdb", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "ushamina@mail.jnu.ac.in", + "name": "Usha Mina", + "typeEntity": "Person" + } + ], + "description": "Curated database of Indian anti-tubercular medicinal plants.", + "editPermission": { + "type": "private" + }, + "function": [ + { + "operation": [ + { + "term": "Database search", + "uri": "http://edamontology.org/operation_2421" + }, + { + "term": "Small molecule design", + "uri": "http://edamontology.org/operation_4009" + }, + { + "term": "Text mining", + "uri": "http://edamontology.org/operation_0306" + } + ] + } + ], + "homepage": "https://www.ammpdb.com/", + "lastUpdate": "2023-10-20T11:34:24.819433Z", + "name": "AMMPDB", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1016/J.JAIM.2023.100712", + "metadata": { + "abstract": "The utilization of medicinal plants for their therapeutic properties has long been a key component of Indian culture. Unique medicinal characteristics can be found in the phytochemicals that are extracted from these plants. Globally, tuberculosis (TB) burden and management are challenged due to the emergence of new resistant strains of Mycobacterium tuberculosis (Mtb). This highlights the importance of new drug molecules from diverse sources as well as their innovative management options. In this context, the present study formulated an Anti Mtb medicinal plant database (AMMPDB Ver. 1.1), a manually curated database of native Indian medicinal plants that reported anti-tubercular (anti-TB) activities and their potential therapeutic phytochemicals. This is the first-ever freely accessible digital repository. The current version of the database provides users, with information regarding 118 native Indian anti-tubercular medicinal plants and their 3374 phytochemicals. The database provides the following information: Taxonomical ID, botanical description, vernacular names, conservation status, geographical distribution maps, IC-50 value, phytochemical details which include - name, Compound ID, Synonyms, location in plant part, 2D, 3D structures (as per the availability), and their medicinal uses reported in the literature. The tools section of the database is equipped with sequentially catalogued and hyperlinked open-access tools utilized for computational drug designing. A case study has been incorporated under the contributors section to validate the tools section and the phytochemicals of the database. AMMPDB Ver 1.1 will be serviceable to research in computational drug designing and discovery with effectiveness and ease. Database URL: https://www.ammpdb.com/", + "authors": [ + { + "name": "Gautam A." + }, + { + "name": "Kanneganti J." + }, + { + "name": "Mina U." + }, + { + "name": "Singh A." + }, + { + "name": "Somvanshi P." + } + ], + "date": "2023-03-01T00:00:00Z", + "journal": "Journal of Ayurveda and Integrative Medicine", + "title": "Anti Mtb Medicinal Plants Database (AMMPDB): A curated database of Indian anti-tubercular medicinal plants" + }, + "pmcid": "PMC10172712", + "pmid": "37120901", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Database portal" + ], + "topic": [ + { + "term": "Data submission, annotation and curation", + "uri": "http://edamontology.org/topic_0219" + }, + { + "term": "Drug metabolism", + "uri": "http://edamontology.org/topic_3375" + }, + { + "term": "Medicinal chemistry", + "uri": "http://edamontology.org/topic_0209" + }, + { + "term": "Medicine", + "uri": "http://edamontology.org/topic_3303" + }, + { + "term": "Plant biology", + "uri": "http://edamontology.org/topic_0780" + } + ] +} diff --git a/data/aodb/aodb.biotools.json b/data/aodb/aodb.biotools.json new file mode 100644 index 0000000000000..3def049042170 --- /dev/null +++ b/data/aodb/aodb.biotools.json @@ -0,0 +1,100 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-20T11:11:34.753463Z", + "biotoolsCURIE": "biotools:aodb", + "biotoolsID": "aodb", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "lingwang@scut.edu.cn", + "name": "Ling Wang" + } + ], + "description": "A comprehensive database for antioxidants including small molecules, peptides and proteins.", + "editPermission": { + "type": "public" + }, + "function": [ + { + "operation": [ + { + "term": "Data retrieval", + "uri": "http://edamontology.org/operation_2422" + }, + { + "term": "Database search", + "uri": "http://edamontology.org/operation_2421" + }, + { + "term": "Protein signal peptide detection", + "uri": "http://edamontology.org/operation_0418" + } + ] + } + ], + "homepage": "https://aodb.idruglab.cn/", + "lastUpdate": "2023-10-20T11:11:34.768498Z", + "name": "AODB", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1016/J.FOODCHEM.2023.135992", + "metadata": { + "abstract": "Antioxidants are widely used in the fields of food, medicine, nutraceuticals, and cosmetics. Given their important roles in promoting and maintaining human health, a large number of antioxidants have been reported. Some antioxidant-related databases have been developed; however, the annotation of antioxidants and related information stored in existing databases is incomplete and requires more efficient retrieval methods. This study aimed to develop a manually curated comprehensive antioxidant database (AODB). Currently, it stores 56,666 small molecules tested for antioxidant activity, 1480 antioxidant peptides, and 998 antioxidant proteins, including their structures, names, antioxidant assay records, computable physicochemical and ADMET properties, and sources. AODB supports text search and mining, 2D and 3D chemical structure search, and BLAST-based protein sequence search, enabling users to retrieve antioxidant data quickly and easily. AODB, as a one-stop antioxidant database, can facilitate the exploration of antioxidants and potential applications. AODB is publicly available and updated annually at https://aodb.idruglab.cn/.", + "authors": [ + { + "name": "Chen Y." + }, + { + "name": "Deng W." + }, + { + "name": "Sun X." + }, + { + "name": "Wang L." + } + ], + "citationCount": 3, + "date": "2023-08-30T00:00:00Z", + "journal": "Food Chemistry", + "title": "AODB: A comprehensive database for antioxidants including small molecules, peptides and proteins" + }, + "pmid": "37001349", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Database portal" + ], + "topic": [ + { + "term": "Cardiology", + "uri": "http://edamontology.org/topic_3335" + }, + { + "term": "Molecular biology", + "uri": "http://edamontology.org/topic_3047" + }, + { + "term": "Nutritional science", + "uri": "http://edamontology.org/topic_3390" + }, + { + "term": "Pharmacology", + "uri": "http://edamontology.org/topic_0202" + }, + { + "term": "Small molecules", + "uri": "http://edamontology.org/topic_0154" + } + ] +} diff --git a/data/atlasxploretm/atlasxploretm.biotools.json b/data/atlasxploretm/atlasxploretm.biotools.json new file mode 100644 index 0000000000000..ed5e1e3a01bd3 --- /dev/null +++ b/data/atlasxploretm/atlasxploretm.biotools.json @@ -0,0 +1,109 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-17T12:28:18.018465Z", + "biotoolsCURIE": "biotools:atlasxploretm", + "biotoolsID": "atlasxploretm", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "liyawang6@gmail.com", + "name": "Liya Wang", + "orcidid": "https://orcid.org/0000-0001-6810-1332", + "typeEntity": "Person" + } + ], + "description": "Web platform for visualizing and sharing spatial epigenome data.", + "documentation": [ + { + "type": [ + "User manual" + ], + "url": "https://docs.atlasxomics.com/projects/AtlasXplore/en/latest/index.html" + } + ], + "editPermission": { + "type": "public" + }, + "function": [ + { + "operation": [ + { + "term": "Visualisation", + "uri": "http://edamontology.org/operation_0337" + } + ] + } + ], + "homepage": "https://web.atlasxomics.com", + "language": [ + "Python", + "R" + ], + "lastUpdate": "2023-10-17T12:28:18.021169Z", + "license": "MIT", + "link": [ + { + "type": [ + "Repository" + ], + "url": "https://github.com/atlasxomics" + } + ], + "name": "AtlasXploreTM", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1093/bioinformatics/btad447", + "metadata": { + "abstract": "Motivation: In recent years, a growing number of spatial epigenome datasets have been generated, presenting rich opportunities for studying the regulation mechanisms in solid tissue sections. However, visual exploration of these datasets requires extensive computational processing of raw data, presenting a challenge for researchers without advanced computational skills to fully explore and analyze such datasets. Results: Here, we introduce AtlasXplore, a web-based platform that enables scientists to interactively navigate a growing collection of spatial epigenome data using an expanding set of tools.", + "authors": [ + { + "name": "Barnett J." + }, + { + "name": "Jafar T." + }, + { + "name": "Rao P." + }, + { + "name": "Silverman J." + }, + { + "name": "Sotudeh N." + }, + { + "name": "Wang L." + } + ], + "date": "2023-08-01T00:00:00Z", + "journal": "Bioinformatics", + "title": "AtlasXplore: a web platform for visualizing and sharing spatial epigenome data" + }, + "pmcid": "PMC10394123", + "pmid": "37478350", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Web application" + ], + "topic": [ + { + "term": "Epigenomics", + "uri": "http://edamontology.org/topic_3173" + }, + { + "term": "Imaging", + "uri": "http://edamontology.org/topic_3382" + } + ] +} diff --git a/data/bakta/bakta.biotools.json b/data/bakta/bakta.biotools.json index 55a4e5e60af88..4397a55aeac64 100644 --- a/data/bakta/bakta.biotools.json +++ b/data/bakta/bakta.biotools.json @@ -165,7 +165,7 @@ "language": [ "Python" ], - "lastUpdate": "2023-02-28T13:37:28.434982Z", + "lastUpdate": "2023-10-17T07:13:30.293759Z", "license": "GPL-3.0", "link": [ { @@ -204,7 +204,7 @@ { "doi": "10.1099/mgen.0.000685", "metadata": { - "abstract": "© 2021 The Authors.Command-line annotation software tools have continuously gained popularity compared to centralized online services due to the worldwide increase of sequenced bacterial genomes. However, results of existing command-line software pipelines heavily depend on taxon-specific databases or sufficiently well annotated reference genomes. Here, we introduce Bakta, a new command-line software tool for the robust, taxon-independent, thorough and, nonetheless, fast annotation of bacterial genomes. Bakta conducts a comprehensive annotation workflow including the detection of small proteins taking into account replicon metadata. The annotation of coding sequences is accelerated via an alignment-free sequence identification approach that in addition facilitates the precise assignment of public database cross-references. Annotation results are exported in GFF3 and International Nucleotide Sequence Database Collaboration (INSDC)-compliant flat files, as well as comprehensive JSON files, facilitating automated downstream analysis. We compared Bakta to other rapid contemporary command-line annotation software tools in both targeted and taxonomically broad benchmarks including isolates and metagenomic-assembled genomes. We demonstrated that Bakta outperforms other tools in terms of functional annotations, the assignment of functional categories and database cross-references, whilst providing comparable wall-clock runtimes. Bakta is implemented in Python 3 and runs on MacOS and Linux systems. It is freely available under a GPLv3 license at https://​github.​com/​oschwengers/​bakta. An accompanying web version is available at https://​bakta.​computational.​bio.", + "abstract": "Command-line annotation software tools have continuously gained popularity compared to centralized online services due to the worldwide increase of sequenced bacterial genomes. However, results of existing command-line software pipelines heavily depend on taxon-specific databases or sufficiently well annotated reference genomes. Here, we introduce Bakta, a new command-line software tool for the robust, taxon-independent, thorough and, nonetheless, fast annotation of bacterial genomes. Bakta conducts a comprehensive annotation workflow including the detection of small proteins taking into account replicon metadata. The annotation of coding sequences is accelerated via an alignment-free sequence identification approach that in addition facilitates the precise assignment of public database cross-references. Annotation results are exported in GFF3 and International Nucleotide Sequence Database Collaboration (INSDC)-compliant flat files, as well as comprehensive JSON files, facilitating automated downstream analysis. We compared Bakta to other rapid contemporary command-line annotation software tools in both targeted and taxonomically broad benchmarks including isolates and metagenomic-assembled genomes. We demonstrated that Bakta outperforms other tools in terms of functional annotations, the assignment of functional categories and database cross-references, whilst providing comparable wall-clock runtimes. Bakta is implemented in Python 3 and runs on MacOS and Linux systems. It is freely available under a GPLv3 license at https://​github.​com/​oschwengers/​bakta. An accompanying web version is available at https://​bakta.​computational.​bio.", "authors": [ { "name": "Beyvers S." @@ -225,7 +225,7 @@ "name": "Schwengers O." } ], - "citationCount": 21, + "citationCount": 87, "date": "2021-01-01T00:00:00Z", "journal": "Microbial Genomics", "title": "Bakta: Rapid and standardized annotation of bacterial genomes via alignment-free sequence identification" @@ -291,6 +291,6 @@ } ], "version": [ - "v1.7.0" + "v1.8.2" ] } diff --git a/data/bhitaic/bhitaic.biotools.json b/data/bhitaic/bhitaic.biotools.json new file mode 100644 index 0000000000000..10e5f0cf20e0c --- /dev/null +++ b/data/bhitaic/bhitaic.biotools.json @@ -0,0 +1,107 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-20T11:29:58.593816Z", + "biotoolsCURIE": "biotools:bhitaic", + "biotoolsID": "bhitaic", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "lucas.a.salas@dartmouth.edu", + "name": "Lucas A Salas", + "orcidid": "https://orcid.org/0000-0002-2279-4097", + "typeEntity": "Person" + } + ], + "description": "Hierarchical tumor artificial intelligence classifier traces tissue of origin and tumor type in primary and metastasized tumors using DNA methylation.", + "editPermission": { + "type": "private" + }, + "function": [ + { + "operation": [ + { + "term": "Gene methylation analysis", + "uri": "http://edamontology.org/operation_3207" + }, + { + "term": "Statistical inference", + "uri": "http://edamontology.org/operation_3658" + } + ] + } + ], + "homepage": "https://sites.dartmouth.edu/salaslabhitaic/", + "language": [ + "Python" + ], + "lastUpdate": "2023-10-20T11:29:58.596343Z", + "name": "bHiTAIC", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1093/NARCAN/ZCAD017", + "metadata": { + "abstract": "Human cancers are heterogenous by their cell composition and origination site. Cancer metastasis generates the conundrum of the unknown origin of migrated tumor cells. Tracing tissue of origin and tumor type in primary and metastasized cancer is vital for clinical significance. DNA methylation alterations play a crucial role in carcinogenesis and mark cell fate differentiation, thus can be used to trace tumor tissue of origin. In this study, we employed a novel tumor-type-specific hierarchical model using genome-scale DNA methylation data to develop a multilayer perceptron model, HiTAIC, to trace tissue of origin and tumor type in 27 cancers from 23 tissue sites in data from 7735 tumors with high resolution, accuracy, and specificity. In tracing primary cancer origin, HiTAIC accuracy was 99% in the test set and 93% in the external validation data set. Metastatic cancers were identified with a 96% accuracy in the external data set. HiTAIC is a user-friendly web-based application through https://sites.dartmouth.edu/salaslabhitaic/. In conclusion, we developed HiTAIC, a DNA methylation-based algorithm, to trace tumor tissue of origin in primary and metastasized cancers. The high accuracy and resolution of tumor tracing using HiTAIC holds promise for clinical assistance in identifying cancer of unknown origin.", + "authors": [ + { + "name": "Christensen B.C." + }, + { + "name": "Levy J.J." + }, + { + "name": "Lu Y." + }, + { + "name": "Salas L.A." + }, + { + "name": "Vosoughi S." + }, + { + "name": "Zhang Z." + } + ], + "date": "2023-06-01T00:00:00Z", + "journal": "NAR Cancer", + "title": "HiTAIC: hierarchical tumor artificial intelligence classifier traces tissue of origin and tumor type in primary and metastasized tumors using DNA methylation" + }, + "pmcid": "PMC10113876", + "pmid": "37089814", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Web application" + ], + "topic": [ + { + "term": "DNA", + "uri": "http://edamontology.org/topic_0654" + }, + { + "term": "Epigenetics", + "uri": "http://edamontology.org/topic_3295" + }, + { + "term": "Gene transcripts", + "uri": "http://edamontology.org/topic_3512" + }, + { + "term": "Machine learning", + "uri": "http://edamontology.org/topic_3474" + }, + { + "term": "Oncology", + "uri": "http://edamontology.org/topic_2640" + } + ] +} diff --git a/data/blaze/blaze.biotools.json b/data/blaze/blaze.biotools.json new file mode 100644 index 0000000000000..6294399bb8e74 --- /dev/null +++ b/data/blaze/blaze.biotools.json @@ -0,0 +1,153 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T19:46:30.952186Z", + "biotoolsCURIE": "biotools:blaze", + "biotoolsID": "blaze", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "michael.clark@unimelb.edu.au", + "name": "Michael B. Clark", + "orcidid": "https://orcid.org/0000-0002-2903-9537", + "typeEntity": "Person" + }, + { + "email": "hee.shim@unimelb.edu.au", + "name": "Heejung Shim", + "typeEntity": "Person" + } + ], + "description": "Identification of cell barcodes from long-read single-cell RNA-seq with BLAZE.", + "editPermission": { + "type": "private" + }, + "function": [ + { + "input": [ + { + "data": { + "term": "RNA sequence", + "uri": "http://edamontology.org/data_3495" + }, + "format": [ + { + "term": "FASTQ", + "uri": "http://edamontology.org/format_1930" + } + ] + } + ], + "operation": [ + { + "term": "Base-calling", + "uri": "http://edamontology.org/operation_3185" + }, + { + "term": "DNA barcoding", + "uri": "http://edamontology.org/operation_3200" + }, + { + "term": "Demultiplexing", + "uri": "http://edamontology.org/operation_3933" + }, + { + "term": "Gene expression profiling", + "uri": "http://edamontology.org/operation_0314" + }, + { + "term": "Quantification", + "uri": "http://edamontology.org/operation_3799" + } + ], + "output": [ + { + "data": { + "term": "Report", + "uri": "http://edamontology.org/data_2048" + }, + "format": [ + { + "term": "CSV", + "uri": "http://edamontology.org/format_3752" + } + ] + } + ] + } + ], + "homepage": "https://github.com/shimlab/BLAZE", + "language": [ + "Python" + ], + "lastUpdate": "2023-10-15T19:46:30.954920Z", + "license": "GPL-3.0", + "name": "BLAZE", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1186/S13059-023-02907-Y", + "metadata": { + "abstract": "Long-read single-cell RNA sequencing (scRNA-seq) enables the quantification of RNA isoforms in individual cells. However, long-read scRNA-seq using the Oxford Nanopore platform has largely relied upon matched short-read data to identify cell barcodes. We introduce BLAZE, which accurately and efficiently identifies 10x cell barcodes using only nanopore long-read scRNA-seq data. BLAZE outperforms the existing tools and provides an accurate representation of the cells present in long-read scRNA-seq when compared to matched short reads. BLAZE simplifies long-read scRNA-seq while improving the results, is compatible with downstream tools accepting a cell barcode file, and is available at https://github.com/shimlab/BLAZE.", + "authors": [ + { + "name": "Clark M.B." + }, + { + "name": "De Paoli-Iseppi R." + }, + { + "name": "Hunt C.P.J." + }, + { + "name": "Parish C.L." + }, + { + "name": "Prawer Y.D.J." + }, + { + "name": "Shim H." + }, + { + "name": "You Y." + } + ], + "citationCount": 2, + "date": "2023-12-01T00:00:00Z", + "journal": "Genome Biology", + "title": "Identification of cell barcodes from long-read single-cell RNA-seq with BLAZE" + }, + "pmcid": "PMC10077662", + "pmid": "37024980", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Script" + ], + "topic": [ + { + "term": "Cell biology", + "uri": "http://edamontology.org/topic_2229" + }, + { + "term": "Gene expression", + "uri": "http://edamontology.org/topic_0203" + }, + { + "term": "RNA", + "uri": "http://edamontology.org/topic_0099" + }, + { + "term": "RNA-Seq", + "uri": "http://edamontology.org/topic_3170" + } + ] +} diff --git a/data/bootranges/bootranges.biotools.json b/data/bootranges/bootranges.biotools.json new file mode 100644 index 0000000000000..378b34f4e5f39 --- /dev/null +++ b/data/bootranges/bootranges.biotools.json @@ -0,0 +1,120 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T17:58:38.767727Z", + "biotoolsCURIE": "biotools:bootranges", + "biotoolsID": "bootranges", + "confidence_flag": "high", + "cost": "Free of charge", + "credit": [ + { + "email": "michaelisaiahlove@gmail.com", + "name": "Michael I Love", + "orcidid": "https://orcid.org/0000-0001-8401-0545", + "typeEntity": "Person" + } + ], + "description": "Flexible generation of null sets of genomic ranges for hypothesis testing.", + "editPermission": { + "type": "private" + }, + "function": [ + { + "operation": [ + { + "term": "Expression correlation analysis", + "uri": "http://edamontology.org/operation_3463" + }, + { + "term": "Gene-set enrichment analysis", + "uri": "http://edamontology.org/operation_2436" + }, + { + "term": "Statistical calculation", + "uri": "http://edamontology.org/operation_2238" + } + ] + } + ], + "homepage": "https://bioconductor.org/packages/nullranges", + "language": [ + "R" + ], + "lastUpdate": "2023-10-15T17:58:38.770321Z", + "license": "GPL-3.0", + "link": [ + { + "type": [ + "Repository" + ], + "url": "https://github.com/Wancen/bootRangespaper" + } + ], + "name": "bootRanges", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1093/BIOINFORMATICS/BTAD190", + "metadata": { + "abstract": "Motivation: Enrichment analysis is a widely utilized technique in genomic analysis that aims to determine if there is a statistically significant association between two sets of genomic features. To conduct this type of hypothesis testing, an appropriate null model is typically required. However, the null distribution that is commonly used can be overly simplistic and may result in inaccurate conclusions. Results: bootRanges provides fast functions for generation of block bootstrapped genomic ranges representing the null hypothesis in enrichment analysis. As part of a modular workflow, bootRanges offers greater flexibility for computing various test statistics leveraging other Bioconductor packages. We show that shuffling or permutation schemes may result in overly narrow test statistic null distributions and over-estimation of statistical significance, while creating new range sets with a block bootstrap preserves local genomic correlation structure and generates more reliable null distributions. It can also be used in more complex analyses, such as accessing correlations between cis-regulatory elements (CREs) and genes across cell types or providing optimized thresholds, e.g. log fold change (logFC) from differential analysis.", + "authors": [ + { + "name": "Davis E.S." + }, + { + "name": "Dozmorov M.G." + }, + { + "name": "Lee S." + }, + { + "name": "Love M.I." + }, + { + "name": "Mu W." + }, + { + "name": "Phanstiel D.H." + } + ], + "date": "2023-05-01T00:00:00Z", + "journal": "Bioinformatics", + "title": "bootRanges: flexible generation of null sets of genomic ranges for hypothesis testing" + }, + "pmcid": "PMC10159650", + "pmid": "37042725", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Library" + ], + "topic": [ + { + "term": "ChIP-seq", + "uri": "http://edamontology.org/topic_3169" + }, + { + "term": "Epigenomics", + "uri": "http://edamontology.org/topic_3173" + }, + { + "term": "GWAS study", + "uri": "http://edamontology.org/topic_3517" + }, + { + "term": "Gene expression", + "uri": "http://edamontology.org/topic_0203" + }, + { + "term": "RNA-Seq", + "uri": "http://edamontology.org/topic_3170" + } + ] +} diff --git a/data/circpcbl/circpcbl.biotools.json b/data/circpcbl/circpcbl.biotools.json new file mode 100644 index 0000000000000..11fec22c567c3 --- /dev/null +++ b/data/circpcbl/circpcbl.biotools.json @@ -0,0 +1,129 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T17:44:47.462088Z", + "biotoolsCURIE": "biotools:circpcbl", + "biotoolsID": "circpcbl", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "zxd@ahau.edu.cn", + "name": "Xiaodan Zhang", + "typeEntity": "Person" + } + ], + "description": "Identification of Plant CircRNAs with a CNN-BiGRU-GLT Model.", + "editPermission": { + "type": "public" + }, + "function": [ + { + "input": [ + { + "data": { + "term": "Nucleic acid sequence", + "uri": "http://edamontology.org/data_2977" + }, + "format": [ + { + "term": "FASTA", + "uri": "http://edamontology.org/format_1929" + } + ] + } + ], + "operation": [ + { + "term": "Nucleic acid sequence analysis", + "uri": "http://edamontology.org/operation_2478" + } + ], + "output": [ + { + "data": { + "term": "Score", + "uri": "http://edamontology.org/data_1772" + }, + "format": [ + { + "term": "CSV", + "uri": "http://edamontology.org/format_3752" + } + ] + } + ] + } + ], + "homepage": "http://www.circpcbl.cn", + "language": [ + "Python" + ], + "lastUpdate": "2023-10-15T17:44:47.464639Z", + "link": [ + { + "type": [ + "Repository" + ], + "url": "https://github.com/Peg-Wu/CircPCBL" + } + ], + "name": "CircPCBL", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.3390/PLANTS12081652", + "metadata": { + "abstract": "Circular RNAs (circRNAs), which are produced post-splicing of pre-mRNAs, are strongly linked to the emergence of several tumor types. The initial stage in conducting follow-up studies involves identifying circRNAs. Currently, animals are the primary target of most established circRNA recognition technologies. However, the sequence features of plant circRNAs differ from those of animal circRNAs, making it impossible to detect plant circRNAs. For example, there are non-GT/AG splicing signals at circRNA junction sites and few reverse complementary sequences and repetitive elements in the flanking intron sequences of plant circRNAs. In addition, there have been few studies on circRNAs in plants, and thus it is urgent to create a plant-specific method for identifying circRNAs. In this study, we propose CircPCBL, a deep-learning approach that only uses raw sequences to distinguish between circRNAs found in plants and other lncRNAs. CircPCBL comprises two separate detectors: a CNN-BiGRU detector and a GLT detector. The CNN-BiGRU detector takes in the one-hot encoding of the RNA sequence as the input, while the GLT detector uses k-mer (k = 1 − 4) features. The output matrices of the two submodels are then concatenated and ultimately pass through a fully connected layer to produce the final output. To verify the generalization performance of the model, we evaluated CircPCBL using several datasets, and the results revealed that it had an F1 of 85.40% on the validation dataset composed of six different plants species and 85.88%, 75.87%, and 86.83% on the three cross-species independent test sets composed of Cucumis sativus, Populus trichocarpa, and Gossypium raimondii, respectively. With an accuracy of 90.9% and 90%, respectively, CircPCBL successfully predicted ten of the eleven circRNAs of experimentally reported Poncirus trifoliata and nine of the ten lncRNAs of rice on the real set. CircPCBL could potentially contribute to the identification of circRNAs in plants. In addition, it is remarkable that CircPCBL also achieved an average accuracy of 94.08% on the human datasets, which is also an excellent result, implying its potential application in animal datasets. Ultimately, CircPCBL is available as a web server, from which the data and source code can also be downloaded free of charge.", + "authors": [ + { + "name": "Huang Z." + }, + { + "name": "Nie Z." + }, + { + "name": "Wu P." + }, + { + "name": "Zhang X." + } + ], + "date": "2023-04-01T00:00:00Z", + "journal": "Plants", + "title": "CircPCBL: Identification of Plant CircRNAs with a CNN-BiGRU-GLT Model" + }, + "pmcid": "PMC10143888", + "pmid": "37111874", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Command-line tool", + "Web application" + ], + "topic": [ + { + "term": "Functional, regulatory and non-coding RNA", + "uri": "http://edamontology.org/topic_0659" + }, + { + "term": "Gene transcripts", + "uri": "http://edamontology.org/topic_3512" + }, + { + "term": "Plant biology", + "uri": "http://edamontology.org/topic_0780" + }, + { + "term": "Zoology", + "uri": "http://edamontology.org/topic_3500" + } + ] +} diff --git a/data/compact/compact.biotools.json b/data/compact/compact.biotools.json new file mode 100644 index 0000000000000..a97e57e533c41 --- /dev/null +++ b/data/compact/compact.biotools.json @@ -0,0 +1,181 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T20:20:02.668413Z", + "biotoolsCURIE": "biotools:compact", + "biotoolsID": "compact", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "Martijn.Huijnen@radboudumc.nl", + "name": "Martijn A. 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Over the last decade, its application has resulted in a large collection of complexome profiling datasets. While computational methods have been developed for the analysis of individual datasets, methods for large-scale comparative analysis of complexomes from multiple species are lacking. Here, we present Comparative Clustering (CompaCt), that performs fully automated integrative analysis of complexome profiling data from multiple species, enabling systematic characterization and comparison of complexomes. CompaCt implements a novel method for leveraging orthology in comparative analysis to allow systematic identification of conserved as well as taxon-specific elements of the analyzed complexomes. We applied this method to a collection of 53 complexome profiles spanning the major branches of the eukaryotes. We demonstrate the ability of CompaCt to robustly identify the composition of protein complexes, and show that integrated analysis of multiple datasets improves characterization of complexes from specific complexome profiles when compared to separate analyses. We identified novel candidate interactors and complexes in a number of species from previously analyzed datasets, like the emp24, the V-ATPase and mitochondrial ATP synthase complexes. Lastly, we demonstrate the utility of CompaCt for the automated large-scale characterization of the complexome of the mosquito Anopheles stephensi shedding light on the evolution of metazoan protein complexes. CompaCt is available from https://github.com/cmbi/compact-bio.", + "authors": [ + { + "name": "Berendsen S.L." + }, + { + "name": "Brandt U." + }, + { + "name": "Cabrera-Orefice A." + }, + { + "name": "Evers F." + }, + { + "name": "Garanto A." + }, + { + "name": "Huynen M.A." + }, + { + "name": "Kooij T.W.A." + }, + { + "name": "Lutikurti M." + }, + { + "name": "Rodenburg R.J." + }, + { + "name": "van Gemert G.-J." + }, + { + "name": "van Strien J." + } + ], + "date": "2023-08-01T00:00:00Z", + "journal": "PLoS Computational Biology", + "title": "Comparative Clustering (CompaCt) of eukaryote complexomes identifies novel interactions and sheds light on protein complex evolution" + }, + "pmcid": "PMC10434966", + "pmid": "37549177", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Command-line tool" + ], + "topic": [ + { + "term": "Evolutionary biology", + "uri": "http://edamontology.org/topic_3299" + }, + { + "term": "Gene and protein families", + "uri": "http://edamontology.org/topic_0623" + }, + { + "term": "Model organisms", + "uri": "http://edamontology.org/topic_0621" + }, + { + "term": "Protein interactions", + "uri": "http://edamontology.org/topic_0128" + }, + { + "term": "Proteomics", + "uri": "http://edamontology.org/topic_0121" + } + ] +} diff --git a/data/dandelion/dandelion.biotools.json b/data/dandelion/dandelion.biotools.json new file mode 100644 index 0000000000000..78020b8f3563e --- /dev/null +++ b/data/dandelion/dandelion.biotools.json @@ -0,0 +1,150 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T20:09:12.519823Z", + "biotoolsCURIE": "biotools:dandelion", + "biotoolsID": "dandelion", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "mrc38@cam.ac.uk", + "name": "Menna R. 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Here we introduce Dandelion, a computational pipeline for scVDJ-seq analysis. It enables the application of standard V(D)J analysis workflows to single-cell datasets, delivering improved V(D)J contig annotation and the identification of nonproductive and partially spliced contigs. We devised a strategy to create an AIR feature space that can be used for both differential V(D)J usage analysis and pseudotime trajectory inference. The application of Dandelion improved the alignment of human thymic development trajectories of double-positive T cells to mature single-positive CD4/CD8 T cells, generating predictions of factors regulating lineage commitment. Dandelion analysis of other cell compartments provided insights into the origins of human B1 cells and ILC/NK cell development, illustrating the power of our approach. Dandelion is available at https://www.github.com/zktuong/dandelion.", + "authors": [ + { + "name": "Clatworthy M.R." + }, + { + "name": "Dann E." + }, + { + "name": "Dratva L.M." + }, + { + "name": "Haniffa M." + }, + { + "name": "Lindeboom R.G.H." + }, + { + "name": "Meyer K.B." + }, + { + "name": "Polanski K." + }, + { + "name": "Suo C." + }, + { + "name": "Teichmann S.A." + }, + { + "name": "Tuong Z.K." + }, + { + "name": "Vento-Tormo R." + }, + { + "name": "Vilarrasa-Blasi R." + } + ], + "citationCount": 2, + "date": "2023-01-01T00:00:00Z", + "journal": "Nature Biotechnology", + "title": "Dandelion uses the single-cell adaptive immune receptor repertoire to explore lymphocyte developmental origins" + }, + "pmid": "37055623", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Library" + ], + "topic": [ + { + "term": "Biotechnology", + "uri": "http://edamontology.org/topic_3297" + }, + { + "term": "Cell biology", + "uri": "http://edamontology.org/topic_2229" + }, + { + "term": "Immunology", + "uri": "http://edamontology.org/topic_0804" + }, + { + "term": "RNA-Seq", + "uri": "http://edamontology.org/topic_3170" + }, + { + "term": "Workflows", + "uri": "http://edamontology.org/topic_0769" + } + ] +} diff --git a/data/deepallodriver/deepallodriver.biotools.json b/data/deepallodriver/deepallodriver.biotools.json new file mode 100644 index 0000000000000..c2a123f78d7f5 --- /dev/null +++ b/data/deepallodriver/deepallodriver.biotools.json @@ -0,0 +1,178 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T17:53:19.991066Z", + "biotoolsCURIE": "biotools:deepallodriver", + "biotoolsID": "deepallodriver", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "Jian.zhang@sjtu.edu.cn", + "name": "Jian Zhang", + "orcidid": "https://orcid.org/0000-0002-6558-791X", + "typeEntity": "Person" + }, + { + "email": "coolist_liu@126.com", + "name": "Xinyi Liu", + "typeEntity": "Person" + }, + { + "email": "jiang.long@shgh.cn", + "name": "Jiang Long", + "typeEntity": "Person" + }, + { + "email": "xuefenglu163@163.com", + "name": "Xuefeng Lu", + "typeEntity": "Person" + } + ], + "description": "Deep learning-based strategy to predict cancer driver mutations.", + "editPermission": { + "type": "public" + }, + "function": [ + { + "input": [ + { + "data": { + "term": "Protein sequence", + "uri": "http://edamontology.org/data_2976" + }, + "format": [ + { + "term": "MAF", + "uri": "http://edamontology.org/format_3008" + } + ] + } + ], + "operation": [ + { + "term": "Small molecule design", + "uri": "http://edamontology.org/operation_4009" + }, + { + "term": "Variant calling", + "uri": "http://edamontology.org/operation_3227" + }, + { + "term": "Variant effect prediction", + "uri": "http://edamontology.org/operation_0331" + } + ], + "output": [ + { + "data": { + "term": "Score", + "uri": "http://edamontology.org/data_1772" + } + } + ] + } + ], + "homepage": "https://mdl.shsmu.edu.cn/DeepAlloDriver", + "lastUpdate": "2023-10-15T17:53:19.993760Z", + "name": "DeepAlloDriver", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1093/NAR/GKAD295", + "metadata": { + "abstract": "Driver mutations can contribute to the initial processes of cancer, and their identification is crucial for understanding tumorigenesis as well as for molecular drug discovery and development. Allostery regulates protein function away from the functional regions at an allosteric site. In addition to the known effects of mutations around functional sites, mutations at allosteric sites have been associated with protein structure, dynamics, and energy communication. As a result, identifying driver mutations at allosteric sites will be beneficial for deciphering the mechanisms of cancer and developing allosteric drugs. In this study, we provided a platform called DeepAlloDriver to predict driver mutations using a deep learning method that exhibited >93% accuracy and precision. Using this server, we found that a missense mutation in RRAS2 (Gln72 to Leu) might serve as an allosteric driver of tumorigenesis, revealing the mechanism of the mutation in knock-in mice and cancer patients. Overall, DeepAlloDriver would facilitate the elucidation of the mechanisms underlying cancer progression and help prioritize cancer therapeutic targets. The web server is freely available at: https://mdl.shsmu.edu.cn/DeepAlloDriver.", + "authors": [ + { + "name": "Gao Q." + }, + { + "name": "Li M." + }, + { + "name": "Li Q." + }, + { + "name": "Liu X." + }, + { + "name": "Long J." + }, + { + "name": "Lu X." + }, + { + "name": "Lu X." + }, + { + "name": "Song K." + }, + { + "name": "Song Q." + }, + { + "name": "Wei J." + }, + { + "name": "Wei J." + }, + { + "name": "Ye Y." + }, + { + "name": "Zha J." + }, + { + "name": "Zhang J." + }, + { + "name": "Zhang L." + }, + { + "name": "Zhang Q." + }, + { + "name": "Zhang Z." + } + ], + "date": "2023-07-05T00:00:00Z", + "journal": "Nucleic Acids Research", + "title": "DeepAlloDriver: A deep learning-based strategy to predict cancer driver mutations" + }, + "pmcid": "PMC10320081", + "pmid": "37078611", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Web application" + ], + "topic": [ + { + "term": "Drug discovery", + "uri": "http://edamontology.org/topic_3336" + }, + { + "term": "Exome sequencing", + "uri": "http://edamontology.org/topic_3676" + }, + { + "term": "Genetic variation", + "uri": "http://edamontology.org/topic_0199" + }, + { + "term": "Oncology", + "uri": "http://edamontology.org/topic_2640" + }, + { + "term": "Transcription factors and regulatory sites", + "uri": "http://edamontology.org/topic_0749" + } + ] +} diff --git a/data/deepcancermap/deepcancermap.biotools.json b/data/deepcancermap/deepcancermap.biotools.json new file mode 100644 index 0000000000000..959567ce015ec --- /dev/null +++ b/data/deepcancermap/deepcancermap.biotools.json @@ -0,0 +1,133 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T17:54:39.534739Z", + "biotoolsCURIE": "biotools:deepcancermap", + "biotoolsID": "deepcancermap", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "jasonwu717@foxmail.com", + "name": "Jingxing Wu" + }, + { + "email": "lingwang@scut.edu.cn", + "name": "Ling Wang", + "orcidid": "https://orcid.org/0000-0001-5116-7749" + } + ], + "description": "Versatile deep learning platform for target- and cell-based anticancer drug discovery.", + "editPermission": { + "type": "private" + }, + "function": [ + { + "input": [ + { + "data": { + "term": "Small molecule structure", + "uri": "http://edamontology.org/data_1463" + }, + "format": [ + { + "term": "SMILES", + "uri": "http://edamontology.org/format_1196" + } + ] + } + ], + "operation": [ + { + "term": "Virtual screening", + "uri": "http://edamontology.org/operation_3938" + } + ], + "output": [ + { + "data": { + "term": "Score", + "uri": "http://edamontology.org/data_1772" + } + } + ] + } + ], + "homepage": "https://deepcancermap.idruglab.cn", + "language": [ + "Python" + ], + "lastUpdate": "2023-10-15T17:54:39.538228Z", + "name": "DeepCancerMap", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1016/J.EJMECH.2023.115401", + "metadata": { + "abstract": "Discovering new anticancer drugs has been widely concerned and remains an open challenge. Target- and phenotypic-based experimental screening represent two mainstream anticancer drug discovery methods, which suffer from time-consuming, labor-intensive, and high experimental costs. In this study, we collected 485,900 compounds involving in 3,919,974 bioactivity records against 426 anticancer targets and 346 cancer cell lines from academic literature, as well as 60 tumor cell lines from NCI-60 panel. A total of 832 classification models (426 target- and 406 cell-based predictive models) were then constructed to predict the inhibitory activity of compounds against targets and tumor cell lines using FP-GNN deep learning method. Compared to the classical machine learning and deep learning methods, the FP-GNN models achieve considerable overall predictive performance, with the highest AUC values of 0.91, 0.88, 0.91 for the test sets of targets, academia-sourced and NCI-60 cancer cell lines, respectively. A user-friendly webserver called DeepCancerMap and its local version were developed based on these high-quality models, enabling users to perform anticancer drug discovery-related tasks including large-scale virtual screening, profiling prediction of anticancer agents, target fishing, and drug repositioning. We anticipate this platform to accelerate the discovery of anticancer drugs in the field. DeepCancerMap is freely available at https://deepcancermap.idruglab.cn.", + "authors": [ + { + "name": "Cai H." + }, + { + "name": "Li Y." + }, + { + "name": "Lin M." + }, + { + "name": "Luo H." + }, + { + "name": "Tang C." + }, + { + "name": "Wang L." + }, + { + "name": "Wu J." + }, + { + "name": "Xiao Y." + }, + { + "name": "Zhao D." + } + ], + "date": "2023-07-05T00:00:00Z", + "journal": "European Journal of Medicinal Chemistry", + "title": "DeepCancerMap: A versatile deep learning platform for target- and cell-based anticancer drug discovery" + }, + "pmid": "37116265" + } + ], + "toolType": [ + "Web application" + ], + "topic": [ + { + "term": "Drug development", + "uri": "http://edamontology.org/topic_3373" + }, + { + "term": "Drug discovery", + "uri": "http://edamontology.org/topic_3336" + }, + { + "term": "Machine learning", + "uri": "http://edamontology.org/topic_3474" + }, + { + "term": "Sequencing", + "uri": "http://edamontology.org/topic_3168" + }, + { + "term": "Small molecules", + "uri": "http://edamontology.org/topic_0154" + } + ] +} diff --git a/data/dnafusion/dnafusion.biotools.json b/data/dnafusion/dnafusion.biotools.json new file mode 100644 index 0000000000000..d9d25032166ad --- /dev/null +++ b/data/dnafusion/dnafusion.biotools.json @@ -0,0 +1,125 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T18:19:50.127772Z", + "biotoolsCURIE": "biotools:dnafusion", + "biotoolsID": "dnafusion", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "boesoere@rm.dk", + "name": "Boe Sandahl Sorensen", + "typeEntity": "Person" + } + ], + "description": "R/Bioconductor package for increased sensitivity of detecting gene fusions in liquid biopsies.", + "editPermission": { + "type": "public" + }, + "function": [ + { + "input": [ + { + "data": { + "term": "Nucleic acid sequence alignment", + "uri": "http://edamontology.org/data_1383" + }, + "format": [ + { + "term": "BAM", + "uri": "http://edamontology.org/format_2572" + } + ] + } + ], + "operation": [ + { + "term": "PCR primer design", + "uri": "http://edamontology.org/operation_0308" + }, + { + "term": "Validation", + "uri": "http://edamontology.org/operation_2428" + }, + { + "term": "Variant calling", + "uri": "http://edamontology.org/operation_3227" + } + ] + } + ], + "homepage": "https://bioconductor.org/packages/DNAfusion", + "language": [ + "R" + ], + "lastUpdate": "2023-10-15T18:19:50.131403Z", + "license": "GPL-3.0", + "link": [ + { + "type": [ + "Repository" + ], + "url": "https://github.com/CTrierMaansson/DNAfusion" + } + ], + "name": "DNAfusion", + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1186/S12859-023-05259-3", + "metadata": { + "abstract": "Background: EML4-ALK gene fusions are oncogenic drivers in non-small cell lung cancer (NSCLC), and liquid biopsies containing EML4-ALK fragments can be used to study tumor dynamics using next-generation sequencing (NGS). However, the sensitivity of EML4-ALK detection varies between pipelines and analysis tools. Results: We developed an R/Bioconductor package, DNAfusion, which can be applied to BAM files generated by commercially available NGS pipelines, such as AVENIO. Forty-eight blood samples from a training cohort consisting of 41 stage IV EML4-ALK-positive NSCLC patients and seven healthy controls were used to develop DNAfusion. DNAfusion detected EML4-ALK in significantly more samples (sensitivity = 61.0%) compared to AVENIO (sensitivity = 36.6%). The newly identified EML4-ALK-positive patients were verified using droplet digital PCR. DNAfusion was subsequently validated in a blinded validation cohort comprising 24 EML4-ALK-positive and 24 EML4-ALK-negative stage IV NSCLC patients. DNAfusion detected significantly more EML4-ALK individuals in the validation cohort (sensitivity = 62.5%) compared to AVENIO (sensitivity = 29.2%). DNAfusion demonstrated a specificity of 100% in both the training and validation cohorts. Conclusion: Here we present DNAfusion, which increases the sensitivity of EML4-ALK detection in liquid biopsies and can be implemented downstream of commercially available NGS pipelines. The simplistic method of operating the R package makes it easy to implement in the clinical setting, enabling wider expansion of NGS-based diagnostics.", + "authors": [ + { + "name": "Andersen E.R." + }, + { + "name": "Maansson C.T." + }, + { + "name": "Meldgaard P." + }, + { + "name": "Sorensen B.S." + }, + { + "name": "Ulhoi M.P." + } + ], + "date": "2023-12-01T00:00:00Z", + "journal": "BMC Bioinformatics", + "title": "DNAfusion: an R/Bioconductor package for increased sensitivity of detecting gene fusions in liquid biopsies" + }, + "pmcid": "PMC10074784", + "pmid": "37016288", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Library" + ], + "topic": [ + { + "term": "Biomarkers", + "uri": "http://edamontology.org/topic_3360" + }, + { + "term": "Gene structure", + "uri": "http://edamontology.org/topic_0114" + }, + { + "term": "Oncology", + "uri": "http://edamontology.org/topic_2640" + }, + { + "term": "Probes and primers", + "uri": "http://edamontology.org/topic_0632" + }, + { + "term": "Sequencing", + "uri": "http://edamontology.org/topic_3168" + } + ] +} diff --git a/data/ebv_gcr/ebv_gcr.biotools.json b/data/ebv_gcr/ebv_gcr.biotools.json new file mode 100644 index 0000000000000..d88e98eefe6d7 --- /dev/null +++ b/data/ebv_gcr/ebv_gcr.biotools.json @@ -0,0 +1,125 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-16T15:33:32.345910Z", + "biotoolsCURIE": "biotools:ebv_gcr", + "biotoolsID": "ebv_gcr", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "jmymryk@uwo.ca", + "name": "Joe S. Mymryk", + "orcidid": "https://orcid.org/0000-0002-3521-8005", + "typeEntity": "Person" + } + ], + "description": "A suite of tools for investigating EBV-associated human gastric carcinogenesis.", + "editPermission": { + "type": "public" + }, + "function": [ + { + "operation": [ + { + "term": "Differential gene expression profiling", + "uri": "http://edamontology.org/operation_3223" + }, + { + "term": "Expression correlation analysis", + "uri": "http://edamontology.org/operation_3463" + }, + { + "term": "Gene methylation analysis", + "uri": "http://edamontology.org/operation_3207" + }, + { + "term": "miRNA expression analysis", + "uri": "http://edamontology.org/operation_3792" + } + ] + } + ], + "homepage": "https://mymryklab.ca/EBV-GCR/ebvgcr-home/", + "language": [ + "R" + ], + "lastUpdate": "2023-10-16T15:33:32.348617Z", + "link": [ + { + "type": [ + "Repository" + ], + "url": "https://github.com/msaland/EBV-GCR-Suite" + } + ], + "name": "EBV-GCR", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.3390/V15040853", + "metadata": { + "abstract": "Epstein-Barr virus (EBV) causes lifelong infection in over 90% of the world’s population. EBV infection leads to several types of B cell and epithelial cancers due to the viral reprogramming of host-cell growth and gene expression. EBV is associated with 10% of stomach/gastric adenocarcinomas (EBVaGCs), which have distinct molecular, pathological, and immunological characteristics compared to EBV-negative gastric adenocarcinomas (EBVnGCs). Publicly available datasets, such as The Cancer Genome Atlas (TCGA), contain comprehensive transcriptomic, genomic, and epigenomic data for thousands of primary human cancer samples, including EBVaGCs. Additionally, single-cell RNA-sequencing data are becoming available for EBVaGCs. These resources provide a unique opportunity to explore the role of EBV in human carcinogenesis, as well as differences between EBVaGCs and their EBVnGC counterparts. We have constructed a suite of web-based tools called the EBV Gastric Cancer Resource (EBV-GCR), which utilizes TCGA and single-cell RNA-seq data and can be used for research related to EBVaGCs. These web-based tools allow investigators to gain in-depth biological and clinical insights by exploring the effects of EBV on cellular gene expression, associations with patient outcomes, immune landscape features, and differential gene methylation, featuring both whole-tissue and single-cell analyses.", + "authors": [ + { + "name": "Christensen E." + }, + { + "name": "Mymryk J.S." + }, + { + "name": "Prusinkiewicz M.A." + }, + { + "name": "Salnikov M.Y." + }, + { + "name": "Shooshtari P." + }, + { + "name": "Wang E." + } + ], + "citationCount": 1, + "date": "2023-04-01T00:00:00Z", + "journal": "Viruses", + "title": "The EBV Gastric Cancer Resource (EBV-GCR): A Suite of Tools for Investigating EBV-Associated Human Gastric Carcinogenesis" + }, + "pmcid": "PMC10145221", + "pmid": "37112833", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Suite", + "Web application" + ], + "topic": [ + { + "term": "Epigenetics", + "uri": "http://edamontology.org/topic_3295" + }, + { + "term": "Functional, regulatory and non-coding RNA", + "uri": "http://edamontology.org/topic_0659" + }, + { + "term": "Immunology", + "uri": "http://edamontology.org/topic_0804" + }, + { + "term": "Oncology", + "uri": "http://edamontology.org/topic_2640" + }, + { + "term": "RNA-Seq", + "uri": "http://edamontology.org/topic_3170" + } + ] +} diff --git a/data/epilepsy_ontology/epilepsy_ontology.biotools.json b/data/epilepsy_ontology/epilepsy_ontology.biotools.json new file mode 100644 index 0000000000000..86c5d960de3e6 --- /dev/null +++ b/data/epilepsy_ontology/epilepsy_ontology.biotools.json @@ -0,0 +1,125 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T20:29:21.757007Z", + "biotoolsCURIE": "biotools:epilepsy_ontology", + "biotoolsID": "epilepsy_ontology", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "alpha.tom.kodamullil@scai.fraunhofer.de", + "name": "Alpha Tom Kodamullil", + "typeEntity": "Person" + } + ], + "description": "Community-based ontology tailored for semantic interoperability and text mining.", + "editPermission": { + "type": "private" + }, + "function": [ + { + "operation": [ + { + "term": "Deposition", + "uri": "http://edamontology.org/operation_3431" + }, + { + "term": "Ontology comparison", + "uri": "http://edamontology.org/operation_3352" + }, + { + "term": "Text mining", + "uri": "http://edamontology.org/operation_0306" + } + ] + } + ], + "homepage": "https://bioportal.bioontology.org/ontologies/EPIO", + "lastUpdate": "2023-10-15T20:29:21.759958Z", + "license": "CC-BY-4.0", + "name": "Epilepsy Ontology", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1093/BIOADV/VBAD033", + "metadata": { + "abstract": "Motivation: Epilepsy is a multifaceted complex disorder that requires a precise understanding of the classification, diagnosis, treatment and disease mechanism governing it. Although scattered resources are available on epilepsy, comprehensive and structured knowledge is missing. In contemplation to promote multidisciplinary knowledge exchange and facilitate advancement in clinical management, especially in pre-clinical research, a disease-specific ontology is necessary. The presented ontology is designed to enable better interconnection between scientific community members in the epilepsy domain. Results: The Epilepsy Ontology (EPIO) is an assembly of structured knowledge on various aspects of epilepsy, developed according to Basic Formal Ontology (BFO) and Open Biological and Biomedical Ontology (OBO) Foundry principles. Concepts and definitions are collected from the latest International League against Epilepsy (ILAE) classification, domain-specific ontologies and scientific literature. This ontology consists of 1879 classes and 28 151 axioms (2171 declaration axioms, 2219 logical axioms) from several aspects of epilepsy. This ontology is intended to be used for data management and text mining purposes. Availability and implementation: The current release of the ontology is publicly available under a Creative Commons 4.0 License and shared via http://purl.obolibrary.org/obo/epso.owl and is a community-based effort assembling various facets of the complex disease. The ontology is also deposited in BioPortal at https://bioportal.bio ontology.org/ontologies/EPIO.", + "authors": [ + { + "name": "Darms J." + }, + { + "name": "Gebel S." + }, + { + "name": "Hofmann-Apitius M." + }, + { + "name": "Jacobs M." + }, + { + "name": "Kaladharan A." + }, + { + "name": "Klein J." + }, + { + "name": "Kodamullil A.T." + }, + { + "name": "Lage-Rupprecht V." + }, + { + "name": "Madan S." + }, + { + "name": "Sargsyan A." + }, + { + "name": "Schultz B." + }, + { + "name": "Sethumadhavan P." + }, + { + "name": "Wegner P." + } + ], + "date": "2023-01-01T00:00:00Z", + "journal": "Bioinformatics Advances", + "title": "The Epilepsy Ontology: a community-based ontology tailored for semantic interoperability and text mining" + }, + "pmcid": "PMC10067149", + "pmid": "37016683", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Ontology" + ], + "topic": [ + { + "term": "Medical informatics", + "uri": "http://edamontology.org/topic_3063" + }, + { + "term": "Natural language processing", + "uri": "http://edamontology.org/topic_0218" + }, + { + "term": "Ontology and terminology", + "uri": "http://edamontology.org/topic_0089" + }, + { + "term": "Pathology", + "uri": "http://edamontology.org/topic_0634" + } + ] +} diff --git a/data/forecast_mpra/forecast_mpra.biotools.json b/data/forecast_mpra/forecast_mpra.biotools.json new file mode 100644 index 0000000000000..9ede249c45c75 --- /dev/null +++ b/data/forecast_mpra/forecast_mpra.biotools.json @@ -0,0 +1,104 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-17T12:33:02.827648Z", + "biotoolsCURIE": "biotools:forecast_mpra", + "biotoolsID": "forecast_mpra", + "confidence_flag": "high", + "cost": "Free of charge", + "credit": [ + { + "email": "thomas.gorochowski@bristol.ac.uk", + "name": "Thomas E Gorochowski", + "orcidid": "https://orcid.org/0000-0003-1702-786X", + "typeEntity": "Person" + } + ], + "description": "Effective design and inference for cell sorting and sequencing based massively parallel reporter assays.", + "editPermission": { + "type": "public" + }, + "function": [ + { + "operation": [ + { + "term": "Network analysis", + "uri": "http://edamontology.org/operation_3927" + }, + { + "term": "Sorting", + "uri": "http://edamontology.org/operation_3802" + }, + { + "term": "Standardisation and normalisation", + "uri": "http://edamontology.org/operation_3435" + } + ] + } + ], + "homepage": "https://gitlab.com/Pierre-Aurelien/forecast", + "language": [ + "Python" + ], + "lastUpdate": "2023-10-17T12:33:02.830323Z", + "license": "MIT", + "link": [ + { + "type": [ + "Repository" + ], + "url": "https://gitlab.com/Pierre-Aurelien/rebeca" + } + ], + "name": "FORECAST", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1093/BIOINFORMATICS/BTAD277", + "metadata": { + "abstract": "Motivation: The ability to measure the phenotype of millions of different genetic designs using Massively Parallel Reporter Assays (MPRAs) has revolutionized our understanding of genotype-to-phenotype relationships and opened avenues for data-centric approaches to biological design. However, our knowledge of how best to design these costly experiments and the effect that our choices have on the quality of the data produced is lacking. Results: In this article, we tackle the issues of data quality and experimental design by developing FORECAST, a Python package that supports the accurate simulation of cell-sorting and sequencing-based MPRAs and robust maximum likelihood-based inference of genetic design function from MPRA data. We use FORECAST’s capabilities to reveal rules for MPRA experimental design that help ensure accurate genotype-to-phenotype links and show how the simulation of MPRA experiments can help us better understand the limits of prediction accuracy when this data are used for training deep learning-based classifiers. As the scale and scope of MPRAs grows, tools like FORECAST will help ensure we make informed decisions during their development and the most of the data produced.", + "authors": [ + { + "name": "Gilliot P.-A." + }, + { + "name": "Gorochowski T.E." + } + ], + "date": "2023-05-01T00:00:00Z", + "journal": "Bioinformatics", + "title": "Effective design and inference for cell sorting and sequencing based massively parallel reporter assays" + }, + "pmcid": "PMC10182853", + "pmid": "37084251", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Command-line tool" + ], + "topic": [ + { + "term": "Genotype and phenotype", + "uri": "http://edamontology.org/topic_0625" + }, + { + "term": "Machine learning", + "uri": "http://edamontology.org/topic_3474" + }, + { + "term": "Proteomics experiment", + "uri": "http://edamontology.org/topic_3520" + }, + { + "term": "Sequencing", + "uri": "http://edamontology.org/topic_3168" + } + ] +} diff --git a/data/frnc/frnc.biotools.json b/data/frnc/frnc.biotools.json new file mode 100644 index 0000000000000..a6ad30198034d --- /dev/null +++ b/data/frnc/frnc.biotools.json @@ -0,0 +1,109 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T17:40:10.761483Z", + "biotoolsCURIE": "biotools:frnc", + "biotoolsID": "frnc", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "jzxu01@stu.edu.cn", + "name": "Jianzhen Xu", + "orcidid": "https://orcid.org/0000-0002-0697-9075", + "typeEntity": "Person" + } + ], + "description": "Systems biology tool to uncover the dynamic spectrum of RBP-ncRNA circuits (RNC) by integrating transcriptomics, interactomics and proteomics data.", + "editPermission": { + "type": "public" + }, + "function": [ + { + "operation": [ + { + "term": "Differential gene expression profiling", + "uri": "http://edamontology.org/operation_3223" + }, + { + "term": "Standardisation and normalisation", + "uri": "http://edamontology.org/operation_3435" + } + ] + } + ], + "homepage": "https://github.com/BioinformaticsSTU/fRNC", + "language": [ + "R" + ], + "lastUpdate": "2023-10-15T17:40:10.764152Z", + "link": [ + { + "type": [ + "Repository" + ], + "url": "https://github.com/BioinformaticsSTU/fRNC" + } + ], + "name": "fRNC", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1016/J.CSBJ.2023.03.035", + "metadata": { + "abstract": "The RNA binding protein (RBP) and non-coding RNA (ncRNA) interacting networks are increasingly recognized as the main mechanism in gene regulation, and are tightly associated with cellular malfunction and disease. Here, we present fRNC, a systems biology tool to uncover the dynamic spectrum of RBP-ncRNA circuits (RNC) by integrating transcriptomics, interactomics and proteomics data. fRNC constructs the RBP-ncRNA network derived from CLIP-seq or PARE experiments. Given scoring on nodes and edges according to differential analysis of expression data, it finds an RNC containing global maximum significant RBPs and ncRNAs. Alternatively, it can also capture the locally maximum scoring RNC according to user-defined starting nodes with the greedy search. When compared with existing tools, fRNC can detect more accurate and robust sub-network with scalability. As shown in the cases of esophageal carcinoma, breast cancer and Alzheimer's disease, fRNC enables users to analyze the collective behaviors between RBP and the interacting ncRNAs, and reveal novel insights into the disease-associated processes. The fRNC R package is available at https://github.com/BioinformaticsSTU/fRNC.", + "authors": [ + { + "name": "Gao X." + }, + { + "name": "Hao S." + }, + { + "name": "Jiang L." + }, + { + "name": "Lin L." + }, + { + "name": "Xu J." + } + ], + "date": "2023-01-01T00:00:00Z", + "journal": "Computational and Structural Biotechnology Journal", + "title": "fRNC: Uncovering the dynamic and condition-specific RBP-ncRNA circuits from multi-omics data" + }, + "pmcid": "PMC10073992", + "pmid": "37035550" + } + ], + "toolType": [ + "Library" + ], + "topic": [ + { + "term": "Functional, regulatory and non-coding RNA", + "uri": "http://edamontology.org/topic_0659" + }, + { + "term": "Gene regulation", + "uri": "http://edamontology.org/topic_0204" + }, + { + "term": "Molecular interactions, pathways and networks", + "uri": "http://edamontology.org/topic_0602" + }, + { + "term": "RNA immunoprecipitation", + "uri": "http://edamontology.org/topic_3794" + }, + { + "term": "Transcriptomics", + "uri": "http://edamontology.org/topic_3308" + } + ] +} diff --git a/data/geneo/geneo.biotools.json b/data/geneo/geneo.biotools.json new file mode 100644 index 0000000000000..4ea9197a5c38f --- /dev/null +++ b/data/geneo/geneo.biotools.json @@ -0,0 +1,120 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-16T14:32:55.465575Z", + "biotoolsCURIE": "biotools:geneo", + "biotoolsID": "geneo", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "ion@engr.uconn.edu", + "name": "Ion I. 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Identification of these neoepitopes from next-generation sequencing data of clinical samples remains challenging and requires the use of complex bioinformatics pipelines. In this paper, we present GeNeo, a bioinformatics toolbox for genomics-guided neoepitope prediction. GeNeo includes a comprehensive set of tools for somatic variant calling and filtering, variant validation, and neoepitope prediction and filtering. For ease of use, GeNeo tools can be accessed via web-based interfaces deployed on a Galaxy portal publicly accessible at https://neo.engr.uconn.edu/. A virtual machine image for running GeNeo locally is also available to academic users upon request.", + "authors": [ + { + "name": "Al Seesi S." + }, + { + "name": "Al-Okaily A." + }, + { + "name": "Alqahtani F.H." + }, + { + "name": "Hagymasi A.T." + }, + { + "name": "Kaur A." + }, + { + "name": "Mandoiu I.I." + }, + { + "name": "Shcheglova T.V." + }, + { + "name": "Sherafat E." + }, + { + "name": "Srivastava P.K." + } + ], + "date": "2023-04-01T00:00:00Z", + "journal": "Journal of Computational Biology", + "title": "GeNeo: A Bioinformatics Toolbox for Genomics-Guided Neoepitope Prediction" + }, + "pmid": "36999902", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Bioinformatics portal", + "Web application" + ], + "topic": [ + { + "term": "Bioinformatics", + "uri": "http://edamontology.org/topic_0091" + }, + { + "term": "Genetic variation", + "uri": "http://edamontology.org/topic_0199" + }, + { + "term": "Imaging", + "uri": "http://edamontology.org/topic_3382" + }, + { + "term": "Oncology", + "uri": "http://edamontology.org/topic_2640" + }, + { + "term": "Vaccinology", + "uri": "http://edamontology.org/topic_3966" + } + ] +} diff --git a/data/haplocov/haplocov.biotools.json b/data/haplocov/haplocov.biotools.json new file mode 100644 index 0000000000000..fdedc7a81bdbe --- /dev/null +++ b/data/haplocov/haplocov.biotools.json @@ -0,0 +1,122 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-17T13:53:24.220029Z", + "biotoolsCURIE": "biotools:haplocov", + "biotoolsID": "haplocov", + "confidence_flag": "high", + "cost": "Free of charge", + "credit": [ + { + "email": "graziano.pesole@uniba.it", + "name": "Graziano Pesole", + "orcidid": "https://orcid.org/0000-0003-3663-0859", + "typeEntity": "Person" + }, + { + "email": "matteo.chiara@unimi.it", + "name": "Matteo Chiara", + "orcidid": "https://orcid.org/0000-0003-3983-4961", + "typeEntity": "Person" + } + ], + "description": "Unsupervised classification and rapid detection of novel emerging variants of SARS-CoV-2.", + "editPermission": { + "type": "private" + }, + "function": [ + { + "operation": [ + { + "term": "Deposition", + "uri": "http://edamontology.org/operation_3431" + }, + { + "term": "Essential dynamics", + "uri": "http://edamontology.org/operation_3891" + }, + { + "term": "Variant calling", + "uri": "http://edamontology.org/operation_3227" + }, + { + "term": "Variant classification", + "uri": "http://edamontology.org/operation_3225" + }, + { + "term": "Variant prioritisation", + "uri": "http://edamontology.org/operation_3226" + } + ] + } + ], + "homepage": "https://github.com/matteo14c/HaploCoV", + "language": [ + "Perl" + ], + "lastUpdate": "2023-10-17T13:53:24.222540Z", + "name": "HaploCoV", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1038/S42003-023-04784-4", + "metadata": { + "abstract": "Accurate and timely monitoring of the evolution of SARS-CoV-2 is crucial for identifying and tracking potentially more transmissible/virulent viral variants, and implement mitigation strategies to limit their spread. Here we introduce HaploCoV, a novel software framework that enables the exploration of SARS-CoV-2 genomic diversity through space and time, to identify novel emerging viral variants and prioritize variants of potential epidemiological interest in a rapid and unsupervised manner. HaploCoV can integrate with any classification/nomenclature and incorporates an effective scoring system for the prioritization of SARS-CoV-2 variants. By performing retrospective analyses of more than 11.5 M genome sequences we show that HaploCoV demonstrates high levels of accuracy and reproducibility and identifies the large majority of epidemiologically relevant viral variants - as flagged by international health authorities – automatically and with rapid turn-around times. Our results highlight the importance of the application of strategies based on the systematic analysis and integration of regional data for rapid identification of novel, emerging variants of SARS-CoV-2. We believe that the approach outlined in this study will contribute to relevant advances to current and future genomic surveillance methods.", + "authors": [ + { + "name": "Chiara M." + }, + { + "name": "Ferrandi E." + }, + { + "name": "Gissi C." + }, + { + "name": "Horner D.S." + }, + { + "name": "Pesole G." + } + ], + "date": "2023-12-01T00:00:00Z", + "journal": "Communications Biology", + "title": "HaploCoV: unsupervised classification and rapid detection of novel emerging variants of SARS-CoV-2" + }, + "pmcid": "PMC10122080", + "pmid": "37087497", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Command-line tool" + ], + "topic": [ + { + "term": "Genomics", + "uri": "http://edamontology.org/topic_0622" + }, + { + "term": "Ontology and terminology", + "uri": "http://edamontology.org/topic_0089" + }, + { + "term": "Phylogeny", + "uri": "http://edamontology.org/topic_0084" + }, + { + "term": "Public health and epidemiology", + "uri": "http://edamontology.org/topic_3305" + }, + { + "term": "Sequence assembly", + "uri": "http://edamontology.org/topic_0196" + } + ] +} diff --git a/data/idhu_ensem/idhu_ensem.biotools.json b/data/idhu_ensem/idhu_ensem.biotools.json new file mode 100644 index 0000000000000..673b84ab8c5a5 --- /dev/null +++ b/data/idhu_ensem/idhu_ensem.biotools.json @@ -0,0 +1,118 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-17T12:14:47.047431Z", + "biotoolsCURIE": "biotools:idhu_ensem", + "biotoolsID": "idhu_ensem", + "confidence_flag": "tool", + "credit": [ + { + "email": "falturise@qu.edu.sa", + "name": "Fahad Alturise", + "orcidid": "https://orcid.org/0000-0001-9176-7984", + "typeEntity": "Person" + } + ], + "description": "Identification of dihydrouridine sites through ensemble learning models.", + "editPermission": { + "type": "public" + }, + "function": [ + { + "input": [ + { + "data": { + "term": "RNA sequence", + "uri": "http://edamontology.org/data_3495" + } + } + ], + "operation": [ + { + "term": "Dimensionality reduction", + "uri": "http://edamontology.org/operation_3935" + }, + { + "term": "PTM site prediction", + "uri": "http://edamontology.org/operation_0417" + }, + { + "term": "tRNA gene prediction", + "uri": "http://edamontology.org/operation_0464" + } + ], + "output": [ + { + "data": { + "term": "Localisation score", + "uri": "http://edamontology.org/data_3756" + } + } + ] + } + ], + "homepage": "https://taseersuleman-idhu-ensem-idhu-ensem.streamlit.app/", + "lastUpdate": "2023-10-17T12:14:47.050447Z", + "name": "iDHU-Ensem", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1177/20552076231165963", + "metadata": { + "abstract": "Background: Dihydrouridine (D) is one of the most significant uridine modifications that have a prominent occurrence in eukaryotes. The folding and conformational flexibility of transfer RNA (tRNA) can be attained through this modification. Objective: The modification also triggers lung cancer in humans. The identification of D sites was carried out through conventional laboratory methods; however, those were costly and time-consuming. The readiness of RNA sequences helps in the identification of D sites through computationally intelligent models. However, the most challenging part is turning these biological sequences into distinct vectors. Methods: The current research proposed novel feature extraction mechanisms and the identification of D sites in tRNA sequences using ensemble models. The ensemble models were then subjected to evaluation using k-fold cross-validation and independent testing. Results: The results revealed that the stacking ensemble model outperformed all the ensemble models by revealing 0.98 accuracy, 0.98 specificity, 0.97 sensitivity, and 0.92 Matthews Correlation Coefficient. The proposed model, iDHU-Ensem, was also compared with pre-existing predictors using an independent test. The accuracy scores have shown that the proposed model in this research study performed better than the available predictors. Conclusion: The current research contributed towards the enhancement of D site identification capabilities through computationally intelligent methods. A web-based server, iDHU-Ensem, was also made available for the researchers at https://taseersuleman-idhu-ensem-idhu-ensem.streamlit.app/.", + "authors": [ + { + "name": "Alkhalifah T." + }, + { + "name": "Alturise F." + }, + { + "name": "Khan Y.D." + }, + { + "name": "Suleman M.T." + } + ], + "citationCount": 1, + "date": "2023-01-01T00:00:00Z", + "journal": "Digital Health", + "title": "iDHU-Ensem: Identification of dihydrouridine sites through ensemble learning models" + }, + "pmcid": "PMC10064468", + "pmid": "37009307", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Web application" + ], + "topic": [ + { + "term": "Functional, regulatory and non-coding RNA", + "uri": "http://edamontology.org/topic_0659" + }, + { + "term": "Machine learning", + "uri": "http://edamontology.org/topic_3474" + }, + { + "term": "Model organisms", + "uri": "http://edamontology.org/topic_0621" + }, + { + "term": "Oncology", + "uri": "http://edamontology.org/topic_2640" + }, + { + "term": "Protein modifications", + "uri": "http://edamontology.org/topic_0601" + } + ] +} diff --git a/data/jasper_gen/jasper_gen.biotools.json b/data/jasper_gen/jasper_gen.biotools.json new file mode 100644 index 0000000000000..1b3d1d08264cb --- /dev/null +++ b/data/jasper_gen/jasper_gen.biotools.json @@ -0,0 +1,88 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T19:31:13.879994Z", + "biotoolsCURIE": "biotools:jasper_gen", + "biotoolsID": "jasper_gen", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "alekseyz@jhu.edu", + "name": "Aleksey V. Zimin", + "orcidid": "https://orcid.org/0000-0001-5091-3092", + "typeEntity": "Person" + } + ], + "description": "A fast genome polishing tool that improves accuracy of genome assemblies.", + "editPermission": { + "type": "public" + }, + "function": [ + { + "operation": [ + { + "term": "De-novo assembly", + "uri": "http://edamontology.org/operation_0524" + }, + { + "term": "Genome assembly", + "uri": "http://edamontology.org/operation_0525" + }, + { + "term": "Variant calling", + "uri": "http://edamontology.org/operation_3227" + }, + { + "term": "k-mer counting", + "uri": "http://edamontology.org/operation_3472" + } + ] + } + ], + "homepage": "https://github.com/alguoo314/JASPER", + "language": [ + "C++", + "Python", + "Shell" + ], + "lastUpdate": "2023-10-15T19:31:13.882508Z", + "license": "GPL-3.0", + "name": "JASPER", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1371/JOURNAL.PCBI.1011032", + "pmcid": "PMC10096238", + "pmid": "37000853", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Command-line tool" + ], + "topic": [ + { + "term": "Genomics", + "uri": "http://edamontology.org/topic_0622" + }, + { + "term": "Plant biology", + "uri": "http://edamontology.org/topic_0780" + }, + { + "term": "Sequence assembly", + "uri": "http://edamontology.org/topic_0196" + }, + { + "term": "Whole genome sequencing", + "uri": "http://edamontology.org/topic_3673" + } + ] +} diff --git a/data/ligbind/ligbind.biotools.json b/data/ligbind/ligbind.biotools.json new file mode 100644 index 0000000000000..c4732a025a6de --- /dev/null +++ b/data/ligbind/ligbind.biotools.json @@ -0,0 +1,130 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T17:56:39.066933Z", + "biotoolsCURIE": "biotools:ligbind", + "biotoolsID": "ligbind", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "2008xypan@sjtu.edu.cn", + "name": "Xiaoyong Pan" + }, + { + "email": "hbshen@sjtu.edu.cn", + "name": "Hong-Bin Shen" + } + ], + "description": "LigBind is a relation-aware framework with graph-level pre-training to enhance the ligand-specific binding residue predictions for 1159 ligands, which can effectively cover the ligands with a few known binding proteins.", + "editPermission": { + "type": "public" + }, + "function": [ + { + "input": [ + { + "data": { + "term": "Protein structure", + "uri": "http://edamontology.org/data_1460" + }, + "format": [ + { + "term": "PDB", + "uri": "http://edamontology.org/format_1476" + } + ] + } + ], + "operation": [ + { + "term": "Ligand-binding site prediction", + "uri": "http://edamontology.org/operation_3897" + }, + { + "term": "Residue distance calculation", + "uri": "http://edamontology.org/operation_2950" + }, + { + "term": "Small molecule design", + "uri": "http://edamontology.org/operation_4009" + } + ], + "output": [ + { + "data": { + "term": "Protein sequence", + "uri": "http://edamontology.org/data_2976" + } + } + ] + } + ], + "homepage": "http://www.csbio.sjtu.edu.cn/bioinf/LigBind/", + "language": [ + "Python" + ], + "lastUpdate": "2023-10-15T17:56:39.069457Z", + "license": "CC-BY-4.0", + "link": [ + { + "type": [ + "Repository" + ], + "url": "https://github.com/YYingXia/LigBind/" + } + ], + "name": "LigBind", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1016/J.JMB.2023.168091", + "metadata": { + "abstract": "Identifying the interactions between proteins and ligands is significant for drug discovery and design. Considering the diverse binding patterns of ligands, the ligand-specific methods are trained per ligand to predict binding residues. However, most of the existing ligand-specific methods ignore shared binding preferences among various ligands and generally only cover a limited number of ligands with a sufficient number of known binding proteins. In this study, we propose a relation-aware framework LigBind with graph-level pre-training to enhance the ligand-specific binding residue predictions for 1159 ligands, which can effectively cover the ligands with a few known binding proteins. LigBind first pre-trains a graph neural network-based feature extractor for ligand-residue pairs and relation-aware classifiers for similar ligands. Then, LigBind is fine-tuned with ligand-specific binding data, where a domain adaptive neural network is designed to automatically leverage the diversity and similarity of various ligand-binding patterns for accurate binding residue prediction. We construct ligand-specific benchmark datasets of 1159 ligands and 16 unseen ligands, which are used to evaluate the effectiveness of LigBind. The results demonstrate the LigBind's efficacy on large-scale ligand-specific benchmark datasets, and it generalizes well to unseen ligands. LigBind also enables accurate identification of the ligand-binding residues in the main protease, papain-like protease and the RNA-dependent RNA polymerase of SARS-CoV-2. The web server and source codes of LigBind are available at http://www.csbio.sjtu.edu.cn/bioinf/LigBind/ and https://github.com/YYingXia/LigBind/ for academic use.", + "authors": [ + { + "name": "Pan X." + }, + { + "name": "Shen H.-B." + }, + { + "name": "Xia Y." + } + ], + "date": "2023-07-01T00:00:00Z", + "journal": "Journal of Molecular Biology", + "title": "LigBind: Identifying Binding Residues for Over 1000 Ligands with Relation-Aware Graph Neural Networks" + }, + "pmid": "37054909", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Web application" + ], + "topic": [ + { + "term": "Drug discovery", + "uri": "http://edamontology.org/topic_3336" + }, + { + "term": "Immunoproteins and antigens", + "uri": "http://edamontology.org/topic_2830" + }, + { + "term": "Machine learning", + "uri": "http://edamontology.org/topic_3474" + }, + { + "term": "Protein interactions", + "uri": "http://edamontology.org/topic_0128" + } + ] +} diff --git a/data/lsppred/lsppred.biotools.json b/data/lsppred/lsppred.biotools.json new file mode 100644 index 0000000000000..1fa718cb7b1b5 --- /dev/null +++ b/data/lsppred/lsppred.biotools.json @@ -0,0 +1,151 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T17:59:04.460025Z", + "biotoolsCURIE": "biotools:lsppred", + "biotoolsID": "lsppred", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "m.doblin@latrobe.edu.au", + "name": "Monika S. Doblin", + "orcidid": "https://orcid.org/0000-0002-8921-2725", + "typeEntity": "Person" + } + ], + "description": "Tool for leaderless secretory protein prediction in plants.", + "editPermission": { + "type": "private" + }, + "function": [ + { + "input": [ + { + "data": { + "term": "Protein sequence", + "uri": "http://edamontology.org/data_2976" + }, + "format": [ + { + "term": "FASTA", + "uri": "http://edamontology.org/format_1929" + } + ] + } + ], + "operation": [ + { + "term": "PTM site prediction", + "uri": "http://edamontology.org/operation_0417" + }, + { + "term": "Protein signal peptide detection", + "uri": "http://edamontology.org/operation_0418" + }, + { + "term": "Subcellular localisation prediction", + "uri": "http://edamontology.org/operation_2489" + } + ], + "output": [ + { + "data": { + "term": "Score", + "uri": "http://edamontology.org/data_1772" + }, + "format": [ + { + "term": "CSV", + "uri": "http://edamontology.org/format_3752" + } + ] + } + ] + } + ], + "homepage": "http://lsppred.lspdb.org", + "language": [ + "Python" + ], + "lastUpdate": "2023-10-15T17:59:04.462864Z", + "license": "GPL-3.0", + "link": [ + { + "type": [ + "Repository" + ], + "url": "https://github.com/LSPtools/LSPpred" + } + ], + "name": "LSPpred", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.3390/PLANTS12071428", + "metadata": { + "abstract": "Plant proteins that are secreted without a classical signal peptide leader sequence are termed leaderless secretory proteins (LSPs) and are implicated in both plant development and (a)biotic stress responses. In plant proteomics experimental workflows, identification of LSPs is hindered by the possibility of contamination from other subcellar compartments upon purification of the secretome. Applying machine learning algorithms to predict LSPs in plants is also challenging due to the rarity of experimentally validated examples for training purposes. This work attempts to address this issue by establishing criteria for identifying potential plant LSPs based on experimental observations and training random forest classifiers on the putative datasets. The resultant plant protein database LSPDB and bioinformatic prediction tools LSPpred and SPLpred are available at lsppred.lspdb.org. The LSPpred and SPLpred modules are internally validated on the training dataset, with false positives controlled at 5%, and are also able to classify the limited number of established plant LSPs (SPLpred (3/4, LSPpred 4/4). Until such time as a larger set of bona fide (independently experimentally validated) LSPs is established using imaging technologies (light/fluorescence/electron microscopy) to confirm sub-cellular location, these tools represent a bridging method for predicting and identifying plant putative LSPs for subsequent experimental validation.", + "authors": [ + { + "name": "Abadia J." + }, + { + "name": "Bacic A." + }, + { + "name": "Ceballos-Laita L." + }, + { + "name": "Davis M.J." + }, + { + "name": "Doblin M.S." + }, + { + "name": "Lonsdale A." + }, + { + "name": "Takahashi D." + }, + { + "name": "Uemura M." + } + ], + "date": "2023-04-01T00:00:00Z", + "journal": "Plants", + "title": "LSPpred Suite: Tools for Leaderless Secretory Protein Prediction in Plants" + }, + "pmcid": "PMC10097205", + "pmid": "37050054" + } + ], + "toolType": [ + "Command-line tool" + ], + "topic": [ + { + "term": "Imaging", + "uri": "http://edamontology.org/topic_3382" + }, + { + "term": "Plant biology", + "uri": "http://edamontology.org/topic_0780" + }, + { + "term": "Proteomics", + "uri": "http://edamontology.org/topic_0121" + }, + { + "term": "Sequence analysis", + "uri": "http://edamontology.org/topic_0080" + }, + { + "term": "Small molecules", + "uri": "http://edamontology.org/topic_0154" + } + ] +} diff --git a/data/morphoscanner2.0/morphoscanner2.0.biotools.json b/data/morphoscanner2.0/morphoscanner2.0.biotools.json new file mode 100644 index 0000000000000..d0939e149fcd7 --- /dev/null +++ b/data/morphoscanner2.0/morphoscanner2.0.biotools.json @@ -0,0 +1,139 @@ +{ + "additionDate": "2023-10-15T17:34:50.309252Z", + "biotoolsCURIE": "biotools:morphoscanner2.0", + "biotoolsID": "morphoscanner2.0", + "confidence_flag": "high", + "credit": [ + { + "email": "f.gelain@css-mendel.it", + "name": "Fabrizio Gelain", + "orcidid": "https://orcid.org/0000-0002-2624-5853", + "typeEntity": "Person" + } + ], + "description": "Python module for analysis of molecular dynamics simulations.", + "editPermission": { + "type": "public" + }, + "function": [ + { + "input": [ + { + "data": { + "term": "Trajectory data", + "uri": "http://edamontology.org/data_3870" + }, + "format": [ + { + "term": "XTC", + "uri": "http://edamontology.org/format_3875" + }, + { + "term": "trr", + "uri": "http://edamontology.org/format_3910" + } + ] + } + ], + "operation": [ + { + "term": "Molecular dynamics", + "uri": "http://edamontology.org/operation_2476" + }, + { + "term": "Simulation analysis", + "uri": "http://edamontology.org/operation_0244" + }, + { + "term": "Structural similarity search", + "uri": "http://edamontology.org/operation_0360" + } + ], + "output": [ + { + "data": { + "term": "Protein property", + "uri": "http://edamontology.org/data_0897" + } + } + ] + } + ], + "homepage": "https://www.cnte.science/software", + "language": [ + "Python" + ], + "lastUpdate": "2023-10-15T17:34:50.312781Z", + "link": [ + { + "type": [ + "Repository" + ], + "url": "https://github.com/lillux/morphoscanner/" + } + ], + "name": "Morphoscanner2.0", + "operatingSystem": [ + "Linux" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1371/JOURNAL.PONE.0284307", + "metadata": { + "abstract": "Molecular dynamics simulations, at different scales, have been exploited for investigating complex mechanisms ruling biologically inspired systems. Nonetheless, with recent advances and unprecedented achievements, the analysis of molecular dynamics simulations requires customized workflows. In 2018, we developed Morphoscanner to retrieve structural relations within self-assembling peptide systems. In particular, we conceived Morphoscanner for tracking the emergence of β-structured domains in self-assembling peptide systems. Here, we introduce Morphoscanner2.0. Morphoscanner2.0 is an object-oriented library for structural and temporal analysis of atomistic and coarse-grained molecular dynamics (CG-MD) simulations written in Python. The library leverages MDAnalysis, PyTorch and NetworkX to perform the pattern recognition of secondary structure patterns, and interfaces with Pandas, Numpy and Matplotlib to make the results accessible to the user. We used Morphoscanner2.0 on both simulation trajectories and protein structures. Because of its dependencies on the MDAnalysis package, Morphoscanner2.0 can read several file formats generated by widely-used molecular simulation packages such as NAMD, Gromacs, OpenMM. Morphoscanner2.0 also includes a routine for tracking the alpha-helix domain formation.", + "authors": [ + { + "name": "Carlino C." + }, + { + "name": "Fontana F." + }, + { + "name": "Gelain F." + }, + { + "name": "Malik A." + } + ], + "citationCount": 1, + "date": "2023-04-01T00:00:00Z", + "journal": "PLoS ONE", + "title": "Morphoscanner2.0: A new python module for analysis of molecular dynamics simulations" + }, + "pmcid": "PMC10138828", + "pmid": "37104393", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Library" + ], + "topic": [ + { + "term": "Biophysics", + "uri": "http://edamontology.org/topic_3306" + }, + { + "term": "Molecular dynamics", + "uri": "http://edamontology.org/topic_0176" + }, + { + "term": "Protein folds and structural domains", + "uri": "http://edamontology.org/topic_0736" + }, + { + "term": "Protein interactions", + "uri": "http://edamontology.org/topic_0128" + }, + { + "term": "Small molecules", + "uri": "http://edamontology.org/topic_0154" + } + ], + "version": [ + "2.0" + ] +} diff --git a/data/mtsviewer/mtsviewer.biotools.json b/data/mtsviewer/mtsviewer.biotools.json new file mode 100644 index 0000000000000..94a95b080718a --- /dev/null +++ b/data/mtsviewer/mtsviewer.biotools.json @@ -0,0 +1,136 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-16T15:28:04.376960Z", + "biotoolsCURIE": "biotools:mtsviewer", + "biotoolsID": "mtsviewer", + "confidence_flag": "high", + "cost": "Free of charge", + "credit": [ + { + "email": "jeanfrancois.trempe@mcgill.ca", + "name": "Jean-François Trempe", + "orcidid": "https://orcid.org/0000-0002-6543-3371", + "typeEntity": "Person" + }, + { + "email": "sali.farhan@mcgill.ca", + "name": "Sali M. K. Farhan", + "typeEntity": "Person" + } + ], + "description": "Database to visualize mitochondrial targeting sequences, cleavage sites, and mutations on protein structures.", + "download": [ + { + "type": "Software package", + "url": "https://zenodo.org/records/7768427" + } + ], + "editPermission": { + "type": "public" + }, + "function": [ + { + "operation": [ + { + "term": "Deposition", + "uri": "http://edamontology.org/operation_3431" + }, + { + "term": "Protein cleavage site prediction", + "uri": "http://edamontology.org/operation_0422" + }, + { + "term": "Protein sequence cleavage", + "uri": "http://edamontology.org/operation_0366" + }, + { + "term": "Protein structure prediction", + "uri": "http://edamontology.org/operation_0474" + }, + { + "term": "Structure visualisation", + "uri": "http://edamontology.org/operation_0570" + } + ] + } + ], + "homepage": "https://neurobioinfo.github.io/MTSvieweR/", + "language": [ + "R" + ], + "lastUpdate": "2023-10-16T15:28:04.379722Z", + "license": "MIT", + "link": [ + { + "type": [ + "Repository" + ], + "url": "https://github.com/neurobioinfo/MTSvieweR" + } + ], + "name": "MTSviewer", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1371/JOURNAL.PONE.0284541", + "metadata": { + "abstract": "Mitochondrial dysfunction is implicated in a wide array of human diseases ranging from neurodegenerative disorders to cardiovascular defects. The coordinated localization and import of proteins into mitochondria are essential processes that ensure mitochondrial homeostasis. The localization and import of most mitochondrial proteins are driven by N-terminal mitochondrial targeting sequences (MTS's), which interact with import machinery and are removed by the mitochondrial processing peptidase (MPP). The recent discovery of internal MTS's-those which are distributed throughout a protein and act as import regulators or secondary MPP cleavage sites-has expanded the role of both MTS's and MPP beyond conventional N-terminal regulatory pathways. Still, the global mutational landscape of MTS's remains poorly characterized, both from genetic and structural perspectives. To this end, we have integrated a variety of tools into one harmonized R/Shiny database called MTSviewer (https://neurobioinfo.github.io/MTSvieweR/), which combines MTS predictions, cleavage sites, genetic variants, pathogenicity predictions, and N-terminomics data with structural visualization using AlphaFold models of human and yeast mitochondrial proteomes. Using MTSviewer, we profiled all MTS-containing proteins across human and yeast mitochondrial proteomes and provide multiple case studies to highlight the utility of this database.", + "authors": [ + { + "name": "Amiri S." + }, + { + "name": "Bayne A.N." + }, + { + "name": "Dong J." + }, + { + "name": "Farhan S.M.K." + }, + { + "name": "Trempe J.-F." + } + ], + "date": "2023-04-01T00:00:00Z", + "journal": "PLoS ONE", + "title": "MTSviewer: A database to visualize mitochondrial targeting sequences, cleavage sites, and mutations on protein structures" + }, + "pmcid": "PMC10124841", + "pmid": "37093842", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Web application" + ], + "topic": [ + { + "term": "Cell biology", + "uri": "http://edamontology.org/topic_2229" + }, + { + "term": "Genetic variation", + "uri": "http://edamontology.org/topic_0199" + }, + { + "term": "Model organisms", + "uri": "http://edamontology.org/topic_0621" + }, + { + "term": "Proteomics", + "uri": "http://edamontology.org/topic_0121" + }, + { + "term": "Sequence analysis", + "uri": "http://edamontology.org/topic_0080" + } + ] +} diff --git a/data/nbthermo/nbthermo.biotools.json b/data/nbthermo/nbthermo.biotools.json new file mode 100644 index 0000000000000..ec765adf5c59c --- /dev/null +++ b/data/nbthermo/nbthermo.biotools.json @@ -0,0 +1,112 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-20T11:45:15.644229Z", + "biotoolsCURIE": "biotools:nbthermo", + "biotoolsID": "nbthermo", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "emoreno@udemedellin.edu.co", + "name": "Ernesto Moreno", + "orcidid": "https://orcid.org/0000-0002-2309-4826", + "typeEntity": "Person" + }, + { + "email": "mariosergiovaldes145@gmail.com", + "name": "Mario S Valdés-Tresanco", + "orcidid": "https://orcid.org/0000-0002-1291-1587", + "typeEntity": "Person" + } + ], + "description": "New thermostability database for nanobodies.", + "editPermission": { + "type": "public" + }, + "function": [ + { + "operation": [ + { + "term": "Literature search", + "uri": "http://edamontology.org/operation_0305" + }, + { + "term": "Standardisation and normalisation", + "uri": "http://edamontology.org/operation_3435" + } + ] + } + ], + "homepage": "https://valdes-tresanco-ms.github.io/NbThermo", + "language": [ + "JavaScript" + ], + "lastUpdate": "2023-10-20T11:45:15.647744Z", + "link": [ + { + "type": [ + "Repository" + ], + "url": "https://github.com/Valdes-Tresanco-MS/NbThermo" + } + ], + "name": "NbThermo", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1093/DATABASE/BAAD021", + "metadata": { + "abstract": "We present NbThermo-a first-in-class database that collects melting temperatures (Tm), amino acid sequences and several other categories of useful data for hundreds of nanobodies (Nbs), compiled from an extensive literature search. This so-far unique database currently contains up-To-date, manually curated data for 564 Nbs. It represents a contribution to efforts aimed at developing new algorithms for reliable Tm prediction to assist Nb engineering for a wide range of applications of these unique biomolecules. Nbs from the two most common source organisms-llama and camel-show similar distributions of melting temperatures. A first exploratory research that takes advantage of this large data collection evidences that understanding the structural bases of Nb thermostability is a complex task, since there are no apparent differences in sequence patterns between the frameworks of Nbs with lower and higher melting temperatures, indicating that the highly variable loops play a relevant role in defining Nb thermostability. Database URL https://valdes-Tresanco-ms.github.io/NbThermo.", + "authors": [ + { + "name": "Molina-Abad E." + }, + { + "name": "Moreno E." + }, + { + "name": "Valdes-Tresanco M.E." + }, + { + "name": "Valdes-Tresanco M.S." + } + ], + "citationCount": 1, + "date": "2023-01-01T00:00:00Z", + "journal": "Database", + "title": "NbThermo: A new thermostability database for nanobodies" + }, + "pmcid": "PMC10091358", + "pmid": "37042467", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Database portal" + ], + "topic": [ + { + "term": "Data submission, annotation and curation", + "uri": "http://edamontology.org/topic_0219" + }, + { + "term": "Literature and language", + "uri": "http://edamontology.org/topic_3068" + }, + { + "term": "Sequencing", + "uri": "http://edamontology.org/topic_3168" + }, + { + "term": "Small molecules", + "uri": "http://edamontology.org/topic_0154" + } + ] +} diff --git a/data/parett/parett.biotools.json b/data/parett/parett.biotools.json new file mode 100644 index 0000000000000..fdb0a0744fb53 --- /dev/null +++ b/data/parett/parett.biotools.json @@ -0,0 +1,109 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T18:02:30.343430Z", + "biotoolsCURIE": "biotools:parett", + "biotoolsID": "parett", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "leclercq.l.s@gmail.com", + "name": "Louis-Stéphane Le Clercq", + "orcidid": "https://orcid.org/0000-0002-8713-8920", + "typeEntity": "Person" + } + ], + "description": "A Python package for the automated retrieval and management of divergence time data from the timeTree resource for downstream analyses.", + "editPermission": { + "type": "private" + }, + "function": [ + { + "operation": [ + { + "term": "Data retrieval", + "uri": "http://edamontology.org/operation_2422" + }, + { + "term": "Genotyping", + "uri": "http://edamontology.org/operation_3196" + }, + { + "term": "Tree dating", + "uri": "http://edamontology.org/operation_3942" + }, + { + "term": "Visualisation", + "uri": "http://edamontology.org/operation_0337" + } + ] + } + ], + "homepage": "https://github.com/LSLeClercq/PAReTT", + "language": [ + "Python" + ], + "lastUpdate": "2023-10-15T18:02:30.346066Z", + "license": "Apache-2.0", + "name": "PAReTT", + "operatingSystem": [ + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1007/S00239-023-10106-3", + "metadata": { + "abstract": "Evolutionary processes happen gradually over time and are, thus, considered time dependent. In addition, several evolutionary processes are either adaptations to local habitats or changing habitats, otherwise restricted thereby. Since evolutionary processes driving speciation take place within the landscape of environmental and temporal bounds, several published studies have aimed at providing accurate, fossil-calibrated, estimates of the divergence times of both extant and extinct species. Correct calibration is critical towards attributing evolutionary adaptations and speciation both to the time and paleogeography that contributed to it. Data from more than 4000 studies and nearly 1,50,000 species are available from a central TimeTree resource and provide opportunities of retrieving divergence times, evolutionary timelines, and time trees in various formats for most vertebrates. These data greatly enhance the ability of researchers to investigate evolution. However, there is limited functionality when studying lists of species that require batch retrieval. To overcome this, a PYTHON package termed Python-Automated Retrieval of TimeTree data (PAReTT) was created to facilitate a biologist-friendly interaction with the TimeTree resource. Here, we illustrate the use of the package through three examples that includes the use of timeline data, time tree data, and divergence time data. Furthermore, PAReTT was previously used in a meta-analysis of candidate genes to illustrate the relationship between divergence times and candidate genes of migration. The PAReTT package is available for download from GitHub or as a pre-compiled Windows executable, with extensive documentation on the package available on GitHub wiki pages regarding dependencies, installation, and implementation of the various functions.", + "authors": [ + { + "name": "Dalton D.L." + }, + { + "name": "Grobler J.P." + }, + { + "name": "Kotze A." + }, + { + "name": "Le Clercq L.-S." + } + ], + "date": "2023-08-01T00:00:00Z", + "journal": "Journal of Molecular Evolution", + "title": "PAReTT: A Python Package for the Automated Retrieval and Management of Divergence Time Data from the TimeTree Resource for Downstream Analyses" + }, + "pmcid": "PMC10277261", + "pmid": "37079046", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Command-line tool", + "Library" + ], + "topic": [ + { + "term": "Mathematics", + "uri": "http://edamontology.org/topic_3315" + }, + { + "term": "Model organisms", + "uri": "http://edamontology.org/topic_0621" + }, + { + "term": "Molecular evolution", + "uri": "http://edamontology.org/topic_3945" + }, + { + "term": "Phylogeny", + "uri": "http://edamontology.org/topic_0084" + }, + { + "term": "Zoology", + "uri": "http://edamontology.org/topic_3500" + } + ] +} diff --git a/data/parradmeth/parradmeth.biotools.json b/data/parradmeth/parradmeth.biotools.json new file mode 100644 index 0000000000000..217ba225a8dbb --- /dev/null +++ b/data/parradmeth/parradmeth.biotools.json @@ -0,0 +1,86 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-16T14:38:23.011820Z", + "biotoolsCURIE": "biotools:parradmeth", + "biotoolsID": "parradmeth", + "confidence_flag": "tool", + "cost": "Free of charge", + "description": "Identification of diferentially methylated regions on multicore clusters.", + "editPermission": { + "type": "private" + }, + "function": [ + { + "operation": [ + { + "term": "DMR identification", + "uri": "http://edamontology.org/operation_3809" + }, + { + "term": "Regression analysis", + "uri": "http://edamontology.org/operation_3659" + }, + { + "term": "Whole genome methylation analysis", + "uri": "http://edamontology.org/operation_3206" + } + ] + } + ], + "homepage": "https://github.com/UDC-GAC/ParRADMeth", + "language": [ + "C++" + ], + "lastUpdate": "2023-10-16T14:38:23.014390Z", + "license": "GPL-3.0", + "name": "ParRADMeth", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1109/TCBB.2022.3230473", + "metadata": { + "abstract": "The discovery of Differentially Methylated (DM) regions is an important research field in biology, as it can help to anticipate the risk of suffering from specific diseases. Nevertheless, the high computational cost of the bioinformatic tools developed for this purpose prevents their application to large-scale datasets. Hence, much faster tools are required to further progress in this research field. In this work we present ParRADMeth, a parallel tool that applies beta-binomial regression for the identification of these DM regions. It is based on the state-of-the-art sequential tool RADMeth, which proved superior biological accuracy compared to counterparts in previous experimental evaluations. ParRADMeth provides the same DM regions as RADMeth but at significantly reduced runtime thanks to exploiting the compute capabilities of common multicore CPU clusters. For example, our tool is up to 189 times faster for real data experiments on a cluster with 16 nodes, each one containing two eight-core processors. The source code of ParRADMeth, as well as a reference manual, are available at https://github.com/UDC-GAC/ParRADMeth.", + "authors": [ + { + "name": "Fernandez-Fraga A." + }, + { + "name": "Gonzalez-Dominguez J." + }, + { + "name": "Tourino J." + } + ], + "date": "2023-05-01T00:00:00Z", + "journal": "IEEE/ACM Transactions on Computational Biology and Bioinformatics", + "title": "ParRADMeth: Identification of Differentially Methylated Regions on Multicore Clusters" + }, + "pmid": "37015593", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Command-line tool" + ], + "topic": [ + { + "term": "Computational biology", + "uri": "http://edamontology.org/topic_3307" + }, + { + "term": "Methylated DNA immunoprecipitation", + "uri": "http://edamontology.org/topic_3674" + }, + { + "term": "Pathology", + "uri": "http://edamontology.org/topic_0634" + } + ] +} diff --git a/data/pdc/pdc.biotools.json b/data/pdc/pdc.biotools.json new file mode 100644 index 0000000000000..24f50d54bddd9 --- /dev/null +++ b/data/pdc/pdc.biotools.json @@ -0,0 +1,116 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T17:50:22.036189Z", + "biotoolsCURIE": "biotools:pdc", + "biotoolsID": "pdc", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "zcx@umich.edu", + "name": "Chengxin Zhang", + "orcidid": "https://orcid.org/0000-0001-7290-1324", + "typeEntity": "Person" + } + ], + "description": "Highly compact file format to store protein 3D coordinates.", + "editPermission": { + "type": "public" + }, + "function": [ + { + "input": [ + { + "data": { + "term": "Protein structure", + "uri": "http://edamontology.org/data_1460" + }, + "format": [ + { + "term": "PDB", + "uri": "http://edamontology.org/format_1476" + } + ] + } + ], + "operation": [ + { + "term": "Deposition", + "uri": "http://edamontology.org/operation_3431" + }, + { + "term": "Formatting", + "uri": "http://edamontology.org/operation_0335" + }, + { + "term": "Parsing", + "uri": "http://edamontology.org/operation_1812" + }, + { + "term": "Protein geometry calculation", + "uri": "http://edamontology.org/operation_0249" + }, + { + "term": "Protein structure prediction", + "uri": "http://edamontology.org/operation_0474" + } + ] + } + ], + "homepage": "https://github.com/kad-ecoli/pdc", + "language": [ + "C++" + ], + "lastUpdate": "2023-10-15T17:50:22.038723Z", + "license": "BSD-2-Clause", + "name": "PDC", + "operatingSystem": [ + "Linux" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1093/DATABASE/BAAD018", + "metadata": { + "abstract": "Recent improvements in computational and experimental techniques for obtaining protein structures have resulted in an explosion of 3D coordinate data. To cope with the ever-increasing sizes of structure databases, this work proposes the Protein Data Compression (PDC) format, which compresses coordinates and temperature factors of full-Atomic and Cα-only protein structures. Without loss of precision, PDC results in 69% to 78% smaller file sizes than Protein Data Bank (PDB) and macromolecular Crystallographic Information File (mmCIF) files with standard GZIP compression. It uses ∼60% less space than existing compression algorithms specific to macromolecular structures. PDC optionally performs lossy compression with minimal sacrifice of precision, which allows reduction of file sizes by another 79%. Conversion between PDC, mmCIF and PDB formats is typically achieved within 0.02 s. The compactness and fast reading/writing speed of PDC make it valuable for storage and analysis of large quantity of tertiary structural data. Database URL https://github.com/kad-ecoli/pdc.", + "authors": [ + { + "name": "Pyle A.M." + }, + { + "name": "Zhang C." + } + ], + "date": "2023-01-01T00:00:00Z", + "journal": "Database", + "title": "PDC: A highly compact file format to store protein 3D coordinates" + }, + "pmcid": "PMC10069377", + "pmid": "37010520", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Command-line tool" + ], + "topic": [ + { + "term": "Protein structure analysis", + "uri": "http://edamontology.org/topic_2814" + }, + { + "term": "Proteomics", + "uri": "http://edamontology.org/topic_0121" + }, + { + "term": "Small molecules", + "uri": "http://edamontology.org/topic_0154" + }, + { + "term": "Structure prediction", + "uri": "http://edamontology.org/topic_0082" + } + ] +} diff --git a/data/phy5/phy5.biotools.json b/data/phy5/phy5.biotools.json new file mode 100644 index 0000000000000..b8321c4aab2cd --- /dev/null +++ b/data/phy5/phy5.biotools.json @@ -0,0 +1,131 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-16T14:45:09.701981Z", + "biotoolsCURIE": "biotools:phy5", + "biotoolsID": "phy5", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "nakano.yoshio70@nihon-u.ac.jp", + "name": "Yoshio Nakano", + "orcidid": "https://orcid.org/0000-0001-9848-3124", + "typeEntity": "Person" + } + ], + "description": "Phylogenetic trees of closely related bacterial species and subspecies based on frequencies of short nucleotide sequences.", + "editPermission": { + "type": "private" + }, + "function": [ + { + "input": [ + { + "data": { + "term": "Nucleic acid sequence", + "uri": "http://edamontology.org/data_2977" + }, + "format": [ + { + "term": "FASTA", + "uri": "http://edamontology.org/format_1929" + } + ] + } + ], + "operation": [ + { + "term": "Phylogenetic inference", + "uri": "http://edamontology.org/operation_0323" + }, + { + "term": "Phylogenetic tree bootstrapping", + "uri": "http://edamontology.org/operation_0552" + }, + { + "term": "Phylogenetic tree comparison", + "uri": "http://edamontology.org/operation_0325" + }, + { + "term": "Phylogenetic tree editing", + "uri": "http://edamontology.org/operation_0326" + }, + { + "term": "Sequence distance matrix generation", + "uri": "http://edamontology.org/operation_0289" + } + ] + } + ], + "homepage": "https://phy5.shinyapps.io/Phy5R/", + "language": [ + "R" + ], + "lastUpdate": "2023-10-16T14:46:17.623921Z", + "link": [ + { + "type": [ + "Repository" + ], + "url": "https://github.com/YoshioNakano2021/phy5" + } + ], + "name": "Phy5", + "operatingSystem": [ + "Linux" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1371/JOURNAL.PONE.0268847", + "metadata": { + "abstract": "Bacterial phylogenetic analyses are commonly performed to explore the evolutionary relationships among various bacterial species and genera based on their 16S rRNA gene sequences; however, these results are limited by mosaicism, intragenomic heterogeneity, and difficulties in distinguishing between related species. In this study, we aimed to perform genome-wide comparisons of different bacterial species, namely Escherichia coli, Shigella, Yersinia, Klebsiella, and Neisseria spp., based on their K-mer profiles to construct phylogenetic trees. Pentanucleotide frequency analyses (512 patterns of 5 nucleotides each) were performed to distinguish between highly similar species. Moreover, Escherichia albertii strains were clearly distinguished from E. coli and Shigella, despite being closely related to enterohemorrhagic E. coli in the phylogenetic tree. In addition, our phylogenetic tree of Ipomoea species based on pentamer frequency in chloroplast genomes was correlated with previously reported morphological similarities. Furthermore, a support vector machine clearly classified E. coli and Shigella genomes based on their pentanucleotide profiles. These results suggest that phylogenetic analyses based on penta- or hexamer profiles are a useful methodology for microbial phylogenetic studies. 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Plasmid maps are used to plan, design, share and publish critical information about gene cloning experiments. PlasMapper 3.0 is the successor to PlasMapper 2.0 and offers many features found only in commercial plasmid mapping/editing packages. PlasMapper 3.0 allows users to paste or upload plasmid sequences as input or to upload existing plasmid maps from its large database of >2000 pre-Annotated plasmids (PlasMapDB). This database can be searched by plasmid names, sequence features, restriction sites, preferred host organisms, and sequence length. PlasMapper 3.0 also supports the annotation of new or never-before-seen plasmids using its own feature database that contains common promoters, terminators, regulatory sequences, replication origins, selectable markers and other features found in most cloning plasmids. 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Ancient, or paleo-, polyploidy events are widely distributed across the eukaryotic phylogeny, and the combination of duplicated and lost duplicated genes that these polyploidies produce can confound the identification of orthologous genes between genomes. POInT uses conserved synteny and phylogenetic models to infer orthologous genes between genomes with a shared polyploidy. It also gives confidence estimates for those orthology inferences. POInTbrowse gives both graphical and query-based access to these inferences from 12 different polyploidy events, allowing users to visualize genomic regions produced by polyploidies and perform batch queries for each polyploidy event, downloading genes trees and coding sequences for orthologous genes meeting user-specified criteria. POInTbrowse and the associated data are online at https://wgd.statgen.ncsu.edu .", + "authors": [ + { + "name": "Conant G.C." + }, + { + "name": "Siddiqui M." + } + ], + "date": "2023-12-01T00:00:00Z", + "journal": "BMC Bioinformatics", + "title": "POInTbrowse: orthology prediction and synteny exploration for paleopolyploid genomes" + }, + "pmcid": "PMC10134530", + "pmid": "37106333" + } + ], + "toolType": [ + "Desktop application" + ], + "topic": [ + { + "term": "Gene expression", + "uri": "http://edamontology.org/topic_0203" + }, + { + "term": "Mapping", + "uri": "http://edamontology.org/topic_0102" + }, + { + "term": "Model organisms", + "uri": "http://edamontology.org/topic_0621" + }, + { + "term": "Phylogeny", + "uri": "http://edamontology.org/topic_0084" + }, + { + "term": "Proteomics experiment", + "uri": "http://edamontology.org/topic_3520" + } + ] +} diff --git a/data/poirot/poirot.biotools.json b/data/poirot/poirot.biotools.json new file mode 100644 index 0000000000000..5fecb50ba7bfe --- /dev/null +++ b/data/poirot/poirot.biotools.json @@ -0,0 +1,135 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-16T14:12:35.397108Z", + "biotoolsCURIE": "biotools:poirot", + "biotoolsID": "poirot", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "mpepste@emory.edu", + "name": "Michael P Epstein", + "orcidid": "https://orcid.org/0000-0001-9647-9738", + "typeEntity": "Person" + } + ], + "description": "Powerful test for parent-of-origin effects in unrelated samples leveraging multiple phenotypes.", + "editPermission": { + "type": "public" + }, + "function": [ + { + "input": [ + { + "data": { + "term": "Genotype/phenotype report", + "uri": "http://edamontology.org/data_0920" + }, + "format": [ + { + "term": "TIDE TXT", + "uri": "http://edamontology.org/format_3835" + } + ] + } + ], + "operation": [ + { + "term": "Essential dynamics", + "uri": "http://edamontology.org/operation_3891" + }, + { + "term": "Genotyping", + "uri": "http://edamontology.org/operation_3196" + }, + { + "term": "Haplotype mapping", + "uri": "http://edamontology.org/operation_0487" + }, + { + "term": "Quantification", + "uri": "http://edamontology.org/operation_3799" + }, + { + "term": "Statistical calculation", + "uri": "http://edamontology.org/operation_2238" + } + ], + "output": [ + { + "data": { + "term": "P-value", + "uri": "http://edamontology.org/data_1669" + } + } + ] + } + ], + "homepage": "https://github.com/staylorhead/POIROT-POE", + "language": [ + "R" + ], + "lastUpdate": "2023-10-16T14:12:35.399758Z", + "name": "POIROT", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1093/BIOINFORMATICS/BTAD199", + "metadata": { + "abstract": "Motivation: There is widespread interest in identifying genetic variants that exhibit parent-of-origin effects (POEs) wherein the effect of an allele on phenotype expression depends on its parental origin. POEs can arise from different phenomena including genomic imprinting and have been documented for many complex traits. Traditional tests for POEs require family data to determine parental origins of transmitted alleles. As most genome-wide association studies (GWAS) sample unrelated individuals (where allelic parental origin is unknown), the study of POEs in such datasets requires sophisticated statistical methods that exploit genetic patterns we anticipate observing when POEs exist. We propose a method to improve discovery of POE variants in large-scale GWAS samples that leverages potential pleiotropy among multiple correlated traits often collected in such studies. Our method compares the phenotypic covariance matrix of heterozygotes to homozygotes based on a Robust Omnibus Test. We refer to our method as the Parent of Origin Inference using Robust Omnibus Test (POIROT) of multiple quantitative traits. Results: Through simulation studies, we compared POIROT to a competing univariate variance-based method which considers separate analysis of each phenotype. We observed POIROT to be well-calibrated with improved power to detect POEs compared to univariate methods. POIROT is robust to non-normality of phenotypes and can adjust for population stratification and other confounders. Finally, we applied POIROT to GWAS data from the UK Biobank using BMI and two cholesterol phenotypes. We identified 338 genome-wide significant loci for follow-up investigation.", + "authors": [ + { + "name": "Cutler D.J." + }, + { + "name": "Epstein M.P." + }, + { + "name": "Head S.T." + }, + { + "name": "Leslie E.J." + } + ], + "date": "2023-04-01T00:00:00Z", + "journal": "Bioinformatics", + "title": "POIROT: A powerful test for parent-of-origin effects in unrelated samples leveraging multiple phenotypes" + }, + "pmcid": "PMC10148680", + "pmid": "37067493", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Script" + ], + "topic": [ + { + "term": "Biobank", + "uri": "http://edamontology.org/topic_3337" + }, + { + "term": "DNA polymorphism", + "uri": "http://edamontology.org/topic_2885" + }, + { + "term": "Epigenetics", + "uri": "http://edamontology.org/topic_3295" + }, + { + "term": "GWAS study", + "uri": "http://edamontology.org/topic_3517" + }, + { + "term": "Genotype and phenotype", + "uri": "http://edamontology.org/topic_0625" + } + ] +} diff --git a/data/ppml/ppml.biotools.json b/data/ppml/ppml.biotools.json new file mode 100644 index 0000000000000..7bc64d4ac725e --- /dev/null +++ b/data/ppml/ppml.biotools.json @@ -0,0 +1,138 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T18:29:12.272271Z", + "biotoolsCURIE": "biotools:ppml", + "biotoolsID": "ppml", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "yangfangscu@gmail.com", + "name": "Yang Fang", + "typeEntity": "Person" + }, + { + "email": "zll7376@zzu.edu.cn", + "name": "Linlin Zhang", + "typeEntity": "Person" + } + ], + "description": "Allelic phenotype prediction of phenylketonuria based on the machine learning method.", + "editPermission": { + "type": "public" + }, + "function": [ + { + "input": [ + { + "data": { + "term": "Mutation identifier", + "uri": "http://edamontology.org/data_2538" + } + } + ], + "operation": [ + { + "term": "Data retrieval", + "uri": "http://edamontology.org/operation_2422" + }, + { + "term": "Gene regulatory network prediction", + "uri": "http://edamontology.org/operation_2437" + }, + { + "term": "Genotyping", + "uri": "http://edamontology.org/operation_3196" + } + ], + "output": [ + { + "data": { + "term": "Score", + "uri": "http://edamontology.org/data_1772" + } + } + ] + } + ], + "homepage": "http://www.bioinfogenetics.info/PPML/", + "language": [ + "Python" + ], + "lastUpdate": "2023-10-15T18:29:12.274710Z", + "name": "PPML", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1186/S40246-023-00481-9", + "metadata": { + "abstract": "Background: Phenylketonuria (PKU) is caused by mutations in the phenylalanine hydroxylase (PAH) gene. Our study aimed to predict the phenotype using the allelic genotype. Methods: A total of 1291 PKU patients with 623 various variants were used as the training dataset for predicting allelic phenotypes. We designed a common machine learning framework to predict allelic genotypes associated with the phenotype. Results: We identified 235 different mutations and 623 various allelic genotypes. The features extracted from the structure of mutations and graph properties of the PKU network to predict the phenotype of PKU were named PPML (PKU phenotype predicted by machine learning). The phenotype of PKU was classified into three different categories: classical PKU (cPKU), mild PKU (mPKU) and mild hyperphenylalaninemia (MHP). Three hub nodes (c.728G>A for cPKU, c.721 for mPKU and c.158G>A for HPA) were used as each classification center, and 5 node attributes were extracted from the network graph for machine learning training features. The area under the ROC curve was AUC = 0.832 for cPKU, AUC = 0.678 for mPKU and AUC = 0.874 for MHP. This suggests that PPML is a powerful method to predict allelic phenotypes in PKU and can be used for genetic counseling of PKU families. Conclusions: The web version of PPML predicts PKU allele classification supported by applicable real cases and prediction results. It is an online database that can be used for PKU phenotype prediction http://www.bioinfogenetics.info/PPML/.", + "authors": [ + { + "name": "Fang Y." + }, + { + "name": "Gao J." + }, + { + "name": "Guo Y." + }, + { + "name": "Li X." + }, + { + "name": "Shi Q." + }, + { + "name": "Song L." + }, + { + "name": "Yu H." + }, + { + "name": "Yuan E." + }, + { + "name": "Yuan E." + }, + { + "name": "Zhang L." + }, + { + "name": "Zhao D." + } + ], + "date": "2023-12-01T00:00:00Z", + "journal": "Human Genomics", + "title": "Allelic phenotype prediction of phenylketonuria based on the machine learning method" + }, + "pmcid": "PMC10064562", + "pmid": "37004080", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Web service" + ], + "topic": [ + { + "term": "Genetic variation", + "uri": "http://edamontology.org/topic_0199" + }, + { + "term": "Genotype and phenotype", + "uri": "http://edamontology.org/topic_0625" + }, + { + "term": "Machine learning", + "uri": "http://edamontology.org/topic_3474" + } + ] +} diff --git a/data/pscope/pscope.biotools.json b/data/pscope/pscope.biotools.json new file mode 100644 index 0000000000000..b14dffd335f7e --- /dev/null +++ b/data/pscope/pscope.biotools.json @@ -0,0 +1,152 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T17:45:54.487655Z", + "biotoolsCURIE": "biotools:pscope", + "biotoolsID": "pscope", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "nslavov@northeastern.edu", + "name": "Nikolai Slavov", + "orcidid": "https://orcid.org/0000-0003-2035-1820", + "typeEntity": "Person" + } + ], + "description": "pSCoPE ensures duty-cycle time for analyzing prioritized peptides across all single cells (thus increasing data consistency) while analyzing identifiable peptides at full duty-cycle, thus increasing proteome depth.", + "editPermission": { + "type": "private" + }, + "function": [ + { + "operation": [ + { + "term": "Essential dynamics", + "uri": "http://edamontology.org/operation_3891" + }, + { + "term": "Protein identification", + "uri": "http://edamontology.org/operation_3767" + }, + { + "term": "Protein quantification", + "uri": "http://edamontology.org/operation_3630" + }, + { + "term": "Tag-based peptide identification", + "uri": "http://edamontology.org/operation_3643" + } + ] + } + ], + "homepage": "http://scp.slavovlab.net/pSCoPE", + "language": [ + "R" + ], + "lastUpdate": "2023-10-15T17:45:54.490341Z", + "license": "MIT", + "link": [ + { + "type": [ + "Repository" + ], + "url": "https://github.com/SlavovLab/pSCoPE" + } + ], + "name": "pSCoPE", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1038/S41592-023-01830-1", + "metadata": { + "abstract": "Major aims of single-cell proteomics include increasing the consistency, sensitivity and depth of protein quantification, especially for proteins and modifications of biological interest. Here, to simultaneously advance all these aims, we developed prioritized Single-Cell ProtEomics (pSCoPE). pSCoPE consistently analyzes thousands of prioritized peptides across all single cells (thus increasing data completeness) while maximizing instrument time spent analyzing identifiable peptides, thus increasing proteome depth. These strategies increased the sensitivity, data completeness and proteome coverage over twofold. The gains enabled quantifying protein variation in untreated and lipopolysaccharide-treated primary macrophages. Within each condition, proteins covaried within functional sets, including phagosome maturation and proton transport, similarly across both treatment conditions. This covariation is coupled to phenotypic variability in endocytic activity. pSCoPE also enabled quantifying proteolytic products, suggesting a gradient of cathepsin activities within a treatment condition. pSCoPE is freely available and widely applicable, especially for analyzing proteins of interest without sacrificing proteome coverage. Support for pSCoPE is available at http://scp.slavovlab.net/pSCoPE.", + "authors": [ + { + "name": "Borriello F." + }, + { + "name": "Cox J." + }, + { + "name": "Derks J." + }, + { + "name": "Di Gioia M." + }, + { + "name": "Emmott E." + }, + { + "name": "Huffman R.G." + }, + { + "name": "Khan S." + }, + { + "name": "Khoury L." + }, + { + "name": "Leduc A." + }, + { + "name": "Perlman D.H." + }, + { + "name": "Petelski A.A." + }, + { + "name": "Slavov N." + }, + { + "name": "Specht H." + }, + { + "name": "Wichmann C." + }, + { + "name": "Zanoni I." + } + ], + "citationCount": 6, + "date": "2023-05-01T00:00:00Z", + "journal": "Nature Methods", + "title": "Prioritized mass spectrometry increases the depth, sensitivity and data completeness of single-cell proteomics" + }, + "pmcid": "PMC10172113", + "pmid": "37012480", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Plug-in" + ], + "topic": [ + { + "term": "Genotype and phenotype", + "uri": "http://edamontology.org/topic_0625" + }, + { + "term": "Proteomics", + "uri": "http://edamontology.org/topic_0121" + }, + { + "term": "Proteomics experiment", + "uri": "http://edamontology.org/topic_3520" + }, + { + "term": "Sequence analysis", + "uri": "http://edamontology.org/topic_0080" + }, + { + "term": "Small molecules", + "uri": "http://edamontology.org/topic_0154" + } + ] +} diff --git a/data/pub2tools2023__dravp/pub2tools2023__dravp.biotools.json b/data/pub2tools2023__dravp/pub2tools2023__dravp.biotools.json new file mode 100644 index 0000000000000..133e556361257 --- /dev/null +++ b/data/pub2tools2023__dravp/pub2tools2023__dravp.biotools.json @@ -0,0 +1,122 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T20:24:05.734293Z", + "biotoolsCURIE": "biotools:pub2tools2023__dravp", + "biotoolsID": "pub2tools2023__dravp", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "zhengh18@hotmail.com", + "name": "Heng Zheng", + "orcidid": "https://orcid.org/0000-0002-1810-5842", + "typeEntity": "Person" + }, + { + "email": "lao@cpu.edu.cn", + "name": "Xingzhen Lao", + "typeEntity": "Person" + } + ], + "description": "Comprehensive database of antiviral peptides and proteins.", + "editPermission": { + "type": "public" + }, + "function": [ + { + "operation": [ + { + "term": "Data retrieval", + "uri": "http://edamontology.org/operation_2422" + }, + { + "term": "Peptide database search", + "uri": "http://edamontology.org/operation_3646" + }, + { + "term": "Protein structure prediction", + "uri": "http://edamontology.org/operation_0474" + } + ] + } + ], + "homepage": "http://dravp.cpu-bioinfor.org/", + "language": [ + "JavaScript", + "PHP" + ], + "lastUpdate": "2023-10-15T20:24:05.737114Z", + "link": [ + { + "type": [ + "Repository" + ], + "url": "https://github.com/CPUDRAVP/DRAVP" + } + ], + "name": "DRAVP", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.3390/V15040820", + "metadata": { + "abstract": "Viruses with rapid replication and easy mutation can become resistant to antiviral drug treatment. With novel viral infections emerging, such as the recent COVID-19 pandemic, novel antiviral therapies are urgently needed. Antiviral proteins, such as interferon, have been used for treating chronic hepatitis C infections for decades. Natural-origin antimicrobial peptides, such as defensins, have also been identified as possessing antiviral activities, including direct antiviral effects and the ability to induce indirect immune responses to viruses. To promote the development of antiviral drugs, we constructed a data repository of antiviral peptides and proteins (DRAVP). The database provides general information, antiviral activity, structure information, physicochemical information, and literature information for peptides and proteins. Because most of the proteins and peptides lack experimentally determined structures, AlphaFold was used to predict each antiviral peptide’s structure. A free website for users (http://dravp.cpu-bioinfor.org/, accessed on 30 August 2022) was constructed to facilitate data retrieval and sequence analysis. Additionally, all the data can be accessed from the web interface. The DRAVP database aims to be a useful resource for developing antiviral drugs.", + "authors": [ + { + "name": "Lao X." + }, + { + "name": "Liu Y." + }, + { + "name": "Ma T." + }, + { + "name": "Sun X." + }, + { + "name": "Zheng H." + }, + { + "name": "Zhu Y." + } + ], + "citationCount": 1, + "date": "2023-04-01T00:00:00Z", + "journal": "Viruses", + "title": "DRAVP: A Comprehensive Database of Antiviral Peptides and Proteins" + }, + "pmcid": "PMC10141206", + "pmid": "37112801", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Database portal" + ], + "topic": [ + { + "term": "Biological databases", + "uri": "http://edamontology.org/topic_3071" + }, + { + "term": "Literature and language", + "uri": "http://edamontology.org/topic_3068" + }, + { + "term": "Small molecules", + "uri": "http://edamontology.org/topic_0154" + }, + { + "term": "Transcription factors and regulatory sites", + "uri": "http://edamontology.org/topic_0749" + } + ] +} diff --git a/data/pyphewas_explorer/pyphewas_explorer.biotools.json b/data/pyphewas_explorer/pyphewas_explorer.biotools.json new file mode 100644 index 0000000000000..30bf938791783 --- /dev/null +++ b/data/pyphewas_explorer/pyphewas_explorer.biotools.json @@ -0,0 +1,87 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-17T13:41:50.216940Z", + "biotoolsCURIE": "biotools:pyphewas_explorer", + "biotoolsID": "pyphewas_explorer", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "cikerley84@gmail.com", + "name": "Cailey I Kerley", + "orcidid": "https://orcid.org/0000-0002-0866-8617", + "typeEntity": "Person" + } + ], + "description": "Visualization tool for exploratory analysis of phenome-disease associations.", + "documentation": [ + { + "type": [ + "User manual" + ], + "url": "https://pyphewas.readthedocs.io/en/latest/index.html" + } + ], + "editPermission": { + "type": "public" + }, + "function": [ + { + "operation": [ + { + "term": "Enrichment analysis", + "uri": "http://edamontology.org/operation_3501" + }, + { + "term": "Regression analysis", + "uri": "http://edamontology.org/operation_3659" + }, + { + "term": "Visualisation", + "uri": "http://edamontology.org/operation_0337" + } + ] + } + ], + "homepage": "https://github.com/MASILab/pyPheWAS", + "language": [ + "JavaScript", + "Python" + ], + "lastUpdate": "2023-10-17T13:41:50.219546Z", + "license": "MIT", + "name": "pyPheWAS Explorer", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1093/JAMIAOPEN/OOAD018", + "pmcid": "PMC10070037", + "pmid": "37021295", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Command-line tool" + ], + "topic": [ + { + "term": "Laboratory techniques", + "uri": "http://edamontology.org/topic_3361" + }, + { + "term": "Paediatrics", + "uri": "http://edamontology.org/topic_3418" + }, + { + "term": "Statistics and probability", + "uri": "http://edamontology.org/topic_2269" + } + ] +} diff --git a/data/qunex/qunex.biotools.json b/data/qunex/qunex.biotools.json new file mode 100644 index 0000000000000..dfa4deeaf9e6f --- /dev/null +++ b/data/qunex/qunex.biotools.json @@ -0,0 +1,157 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-17T14:04:08.719531Z", + "biotoolsCURIE": "biotools:qunex", + "biotoolsID": "qunex", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "jielisa.ji@yale.edu", + "name": "Jie Lisa Ji", + "typeEntity": "Person" + } + ], + "description": "Integrative platform for reproducible neuroimaging analytics.", + "documentation": [ + { + "type": [ + "User manual" + ], + "url": "http://qunex.readthedocs.io/" + } + ], + "editPermission": { + "type": "public" + }, + "function": [ + { + "operation": [ + { + "term": "Quantification", + "uri": "http://edamontology.org/operation_3799" + }, + { + "term": "Visualisation", + "uri": "http://edamontology.org/operation_0337" + } + ] + } + ], + "homepage": "http://qunex.yale.edu", + "language": [ + "Bash", + "MATLAB", + "Python", + "R" + ], + "lastUpdate": "2023-10-17T14:04:08.721884Z", + "license": "GPL-1.0", + "name": "QuNex", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.3389/FNINF.2023.1104508", + "metadata": { + "abstract": "Introduction: Neuroimaging technology has experienced explosive growth and transformed the study of neural mechanisms across health and disease. However, given the diversity of sophisticated tools for handling neuroimaging data, the field faces challenges in method integration, particularly across multiple modalities and species. Specifically, researchers often have to rely on siloed approaches which limit reproducibility, with idiosyncratic data organization and limited software interoperability. Methods: To address these challenges, we have developed Quantitative Neuroimaging Environment & Toolbox (QuNex), a platform for consistent end-to-end processing and analytics. QuNex provides several novel functionalities for neuroimaging analyses, including a “turnkey” command for the reproducible deployment of custom workflows, from onboarding raw data to generating analytic features. Results: The platform enables interoperable integration of multi-modal, community-developed neuroimaging software through an extension framework with a software development kit (SDK) for seamless integration of community tools. Critically, it supports high-throughput, parallel processing in high-performance compute environments, either locally or in the cloud. Notably, QuNex has successfully processed over 10,000 scans across neuroimaging consortia, including multiple clinical datasets. Moreover, QuNex enables integration of human and non-human workflows via a cohesive translational platform. Discussion: Collectively, this effort stands to significantly impact neuroimaging method integration across acquisition approaches, pipelines, datasets, computational environments, and species. Building on this platform will enable more rapid, scalable, and reproducible impact of neuroimaging technology across health and disease.", + "authors": [ + { + "name": "Anticevic A." + }, + { + "name": "Coalson T.S." + }, + { + "name": "Demsar J." + }, + { + "name": "Fonteneau C." + }, + { + "name": "Glasser M.F." + }, + { + "name": "Harms M.P." + }, + { + "name": "Helmer M." + }, + { + "name": "Ji J.L." + }, + { + "name": "Kraljic A." + }, + { + "name": "Matkovic A." + }, + { + "name": "Murray J.D." + }, + { + "name": "Pan L." + }, + { + "name": "Purg N." + }, + { + "name": "Repovs G." + }, + { + "name": "Sotiropoulos S.N." + }, + { + "name": "Tamayo Z." + }, + { + "name": "Warrington S." + }, + { + "name": "Winkler A." + }, + { + "name": "Zerbi V." + } + ], + "date": "2023-01-01T00:00:00Z", + "journal": "Frontiers in Neuroinformatics", + "title": "QuNex—An integrative platform for reproducible neuroimaging analytics" + }, + "pmcid": "PMC10113546", + "pmid": "37090033", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Suite" + ], + "topic": [ + { + "term": "Computer science", + "uri": "http://edamontology.org/topic_3316" + }, + { + "term": "MRI", + "uri": "http://edamontology.org/topic_3444" + }, + { + "term": "Medical imaging", + "uri": "http://edamontology.org/topic_3384" + }, + { + "term": "Medical informatics", + "uri": "http://edamontology.org/topic_3063" + }, + { + "term": "Workflows", + "uri": "http://edamontology.org/topic_0769" + } + ] +} diff --git a/data/recetox-msfinder/recetox-msfinder.biotools.json b/data/recetox-msfinder/recetox-msfinder.biotools.json new file mode 100644 index 0000000000000..bbb7f995dfb61 --- /dev/null +++ b/data/recetox-msfinder/recetox-msfinder.biotools.json @@ -0,0 +1,58 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-20T13:11:56.009108Z", + "biotoolsCURIE": "biotools:recetox-msfinder", + "biotoolsID": "recetox-msfinder", + "description": "This is a modified copy of MS-FINDER with source code modifications to make the tool accessible in Galaxy.\n\nMS-FINDER - software for structure elucidation of unknown spectra with hydrogen rearrangement (HR) rules\n\nThe program supports molecular formula prediction, metabolie class prediction, and structure elucidation for EI-MS and MS/MS spectra, and the assembly is licensed under the CC-BY 4.0.", + "editPermission": { + "type": "private" + }, + "function": [ + { + "input": [ + { + "data": { + "term": "Mass spectrometry data", + "uri": "http://edamontology.org/data_2536" + } + } + ], + "operation": [ + { + "term": "Annotation", + "uri": "http://edamontology.org/operation_0226" + } + ], + "output": [ + { + "data": { + "term": "Expression data", + "uri": "http://edamontology.org/data_2603" + } + } + ] + } + ], + "homepage": "https://github.com/RECETOX/recetox-msfinder", + "lastUpdate": "2023-10-20T13:11:56.011800Z", + "license": "CC-BY-4.0", + "link": [ + { + "type": [ + "Galaxy service" + ], + "url": "https://umsa.cerit-sc.cz/root?tool_id=toolshed.g2.bx.psu.edu/repos/recetox/recetox_msfinder/recetox_msfinder/3.5.2+galaxy0" + } + ], + "name": "recetox-msfinder", + "owner": "recetox-specdatri", + "topic": [ + { + "term": "Metabolomics", + "uri": "http://edamontology.org/topic_3172" + } + ], + "version": [ + "v3.5.2-rcx0" + ] +} diff --git a/data/rnacanvas/rnacanvas.biotools.json b/data/rnacanvas/rnacanvas.biotools.json new file mode 100644 index 0000000000000..587097f56363f --- /dev/null +++ b/data/rnacanvas/rnacanvas.biotools.json @@ -0,0 +1,113 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T18:00:48.262410Z", + "biotoolsCURIE": "biotools:rnacanvas", + "biotoolsID": "rnacanvas", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "simona@umd.edu", + "name": "Anne E Simon", + "orcidid": "https://orcid.org/0000-0001-6121-0704", + "typeEntity": "Person" + } + ], + "description": "Interactive drawing and exploration of nucleic acid structures.", + "editPermission": { + "type": "private" + }, + "function": [ + { + "operation": [ + { + "term": "Nucleic acid structure comparison", + "uri": "http://edamontology.org/operation_2518" + }, + { + "term": "Nucleic acid structure prediction", + "uri": "http://edamontology.org/operation_0475" + }, + { + "term": "Structure editing", + "uri": "http://edamontology.org/operation_3080" + }, + { + "term": "Visualisation", + "uri": "http://edamontology.org/operation_0337" + } + ] + } + ], + "homepage": "https://rnacanvas.app", + "language": [ + "JavaScript" + ], + "lastUpdate": "2023-10-15T18:00:48.265428Z", + "license": "MIT", + "link": [ + { + "type": [ + "Repository" + ], + "url": "https://github.com/pzhaojohnson/rnacanvas" + } + ], + "name": "RNAcanvas", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1093/NAR/GKAD302", + "metadata": { + "abstract": "Two-dimensional drawing of nucleic acid structures, particularly RNA structures, is fundamental to the communication of nucleic acids research. However, manually drawing structures is laborious and infeasible for structures thousands of nucleotides long. RNAcanvas automatically arranges residues into strictly shaped stems and loops while providing robust interactive editing features, including click-And-drag layout adjustment. Drawn elements are highly customizable in a point-And-click manner, including colours, fonts, size and shading, flexible numbering, and outlining of bases. Tertiary interactions can be drawn as draggable, curved lines. Leontis-Westhof notation for depicting non-canonical base-pairs is fully supported, as well as text labels for structural features (e.g. hairpins). RNAcanvas also has many unique features and performance optimizations for large structures that cannot be correctly predicted and require manual refinement based on the researcher's own analyses and expertise. To this end, RNAcanvas has point-And-click structure editing with real-Time highlighting of complementary sequences and motif search functionality, novel features that greatly aid in the identification of putative long-range tertiary interactions, de novo analysis of local structures, and phylogenetic comparisons. For ease in producing publication quality figures, drawings can be exported in both SVG and PowerPoint formats. URL: https://rnacanvas.app.", + "authors": [ + { + "name": "Johnson P.Z." + }, + { + "name": "Simon A.E." + } + ], + "citationCount": 1, + "date": "2023-07-05T00:00:00Z", + "journal": "Nucleic Acids Research", + "title": "RNAcanvas: Interactive drawing and exploration of nucleic acid structures" + }, + "pmcid": "PMC10320051", + "pmid": "37094080", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Web application" + ], + "topic": [ + { + "term": "Nucleic acid structure analysis", + "uri": "http://edamontology.org/topic_0097" + }, + { + "term": "Probes and primers", + "uri": "http://edamontology.org/topic_0632" + }, + { + "term": "RNA", + "uri": "http://edamontology.org/topic_0099" + }, + { + "term": "Structure prediction", + "uri": "http://edamontology.org/topic_0082" + }, + { + "term": "Tomography", + "uri": "http://edamontology.org/topic_3452" + } + ] +} diff --git a/data/rnalysis/rnalysis.biotools.json b/data/rnalysis/rnalysis.biotools.json new file mode 100644 index 0000000000000..b0c6c334651a3 --- /dev/null +++ b/data/rnalysis/rnalysis.biotools.json @@ -0,0 +1,191 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T17:47:17.818044Z", + "biotoolsCURIE": "biotools:rnalysis", + "biotoolsID": "rnalysis", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "guyteichman@gmail.com", + "name": "Guy Teichman", + "orcidid": "https://orcid.org/0000-0003-2285-1343", + "typeEntity": "Person" + } + ], + "description": "Python-based software for analyzing RNA sequencing data.", + "documentation": [ + { + "type": [ + "API documentation" + ], + "url": "https://guyteichman.github.io/RNAlysis/build/api_reference.html" + }, + { + "type": [ + "User manual" + ], + "url": "https://guyteichman.github.io/RNAlysis/build/tutorial.html" + } + ], + "editPermission": { + "type": "private" + }, + "function": [ + { + "input": [ + { + "data": { + "term": "Count matrix", + "uri": "http://edamontology.org/data_3917" + }, + "format": [ + { + "term": "TSV", + "uri": "http://edamontology.org/format_3475" + } + ] + }, + { + "data": { + "term": "Nucleic acid sequence", + "uri": "http://edamontology.org/data_2977" + }, + "format": [ + { + "term": "FASTQ-like format (text)", + "uri": "http://edamontology.org/format_2182" + } + ] + } + ], + "operation": [ + { + "term": "Essential dynamics", + "uri": "http://edamontology.org/operation_3891" + }, + { + "term": "Gene-set enrichment analysis", + "uri": "http://edamontology.org/operation_2436" + }, + { + "term": "RNA-Seq quantification", + "uri": "http://edamontology.org/operation_3800" + }, + { + "term": "Sequence trimming", + "uri": "http://edamontology.org/operation_3192" + }, + { + "term": "Visualisation", + "uri": "http://edamontology.org/operation_0337" + } + ], + "output": [ + { + "data": { + "term": "Clustered expression profiles", + "uri": "http://edamontology.org/data_3768" + } + }, + { + "data": { + "term": "GO-term enrichment data", + "uri": "http://edamontology.org/data_3754" + } + }, + { + "data": { + "term": "Gene expression profile", + "uri": "http://edamontology.org/data_0928" + } + }, + { + "data": { + "term": "Pathway overrepresentation data", + "uri": "http://edamontology.org/data_3953" + } + } + ] + } + ], + "homepage": "https://github.com/GuyTeichman/RNAlysis", + "language": [ + "Python" + ], + "lastUpdate": "2023-10-15T17:47:17.820476Z", + "license": "MIT", + "name": "RNAlysis", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1186/S12915-023-01574-6", + "metadata": { + "abstract": "Background: Among the major challenges in next-generation sequencing experiments are exploratory data analysis, interpreting trends, identifying potential targets/candidates, and visualizing the results clearly and intuitively. These hurdles are further heightened for researchers who are not experienced in writing computer code since most available analysis tools require programming skills. Even for proficient computational biologists, an efficient and replicable system is warranted to generate standardized results. Results: We have developed RNAlysis, a modular Python-based analysis software for RNA sequencing data. RNAlysis allows users to build customized analysis pipelines suiting their specific research questions, going all the way from raw FASTQ files (adapter trimming, alignment, and feature counting), through exploratory data analysis and data visualization, clustering analysis, and gene set enrichment analysis. RNAlysis provides a friendly graphical user interface, allowing researchers to analyze data without writing code. We demonstrate the use of RNAlysis by analyzing RNA sequencing data from different studies using C.elegans nematodes. We note that the software applies equally to data obtained from any organism with an existing reference genome. Conclusions: RNAlysis is suitable for investigating various biological questions, allowing researchers to more accurately and reproducibly run comprehensive bioinformatic analyses. It functions as a gateway into RNA sequencing analysis for less computer-savvy researchers, but can also help experienced bioinformaticians make their analyses more robust and efficient, as it offers diverse tools, scalability, automation, and standardization between analyses.", + "authors": [ + { + "name": "Cohen D." + }, + { + "name": "Dunsky N." + }, + { + "name": "Ganon O." + }, + { + "name": "Gingold H." + }, + { + "name": "Rechavi O." + }, + { + "name": "Shani S." + }, + { + "name": "Teichman G." + } + ], + "citationCount": 1, + "date": "2023-12-01T00:00:00Z", + "journal": "BMC Biology", + "title": "RNAlysis: analyze your RNA sequencing data without writing a single line of code" + }, + "pmcid": "PMC10080885", + "pmid": "37024838", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Desktop application", + "Library" + ], + "topic": [ + { + "term": "Gene expression", + "uri": "http://edamontology.org/topic_0203" + }, + { + "term": "Microarray experiment", + "uri": "http://edamontology.org/topic_3518" + }, + { + "term": "RNA", + "uri": "http://edamontology.org/topic_0099" + }, + { + "term": "RNA-Seq", + "uri": "http://edamontology.org/topic_3170" + }, + { + "term": "Workflows", + "uri": "http://edamontology.org/topic_0769" + } + ] +} diff --git a/data/schema_playground/schema_playground.biotools.json b/data/schema_playground/schema_playground.biotools.json new file mode 100644 index 0000000000000..179696a49c4aa --- /dev/null +++ b/data/schema_playground/schema_playground.biotools.json @@ -0,0 +1,141 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-16T14:56:48.439877Z", + "biotoolsCURIE": "biotools:schema_playground", + "biotoolsID": "schema_playground", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "gtsueng@scripps.edu", + "name": "Ginger Tsueng", + "orcidid": "https://orcid.org/0000-0001-9536-9115", + "typeEntity": "Person" + } + ], + "description": "Tool for authoring, extending, and using metadata schemas to improve FAIRness of biomedical data.", + "editPermission": { + "type": "public" + }, + "function": [ + { + "operation": [ + { + "term": "Data retrieval", + "uri": "http://edamontology.org/operation_2422" + }, + { + "term": "Database comparison", + "uri": "http://edamontology.org/operation_3561" + }, + { + "term": "Database search", + "uri": "http://edamontology.org/operation_2421" + }, + { + "term": "Deposition", + "uri": "http://edamontology.org/operation_3431" + }, + { + "term": "Standardisation and normalisation", + "uri": "http://edamontology.org/operation_3435" + } + ] + } + ], + "homepage": "http://Schema.org", + "language": [ + "C++", + "Python" + ], + "lastUpdate": "2023-10-16T14:56:48.442533Z", + "license": "Apache-2.0", + "link": [ + { + "type": [ + "Other" + ], + "url": "https://discovery.biothings.io/schema-playground" + }, + { + "type": [ + "Repository" + ], + "url": "https://github.com/schemaorg/schemaorg" + } + ], + "name": "Schema Playground", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1186/S12859-023-05258-4", + "metadata": { + "abstract": "Background: Biomedical researchers are strongly encouraged to make their research outputs more Findable, Accessible, Interoperable, and Reusable (FAIR). While many biomedical research outputs are more readily accessible through open data efforts, finding relevant outputs remains a significant challenge. Schema.org is a metadata vocabulary standardization project that enables web content creators to make their content more FAIR. Leveraging Schema.org could benefit biomedical research resource providers, but it can be challenging to apply Schema.org standards to biomedical research outputs. We created an online browser-based tool that empowers researchers and repository developers to utilize Schema.org or other biomedical schema projects. Results: Our browser-based tool includes features which can help address many of the barriers towards Schema.org-compliance such as: The ability to easily browse for relevant Schema.org classes, the ability to extend and customize a class to be more suitable for biomedical research outputs, the ability to create data validation to ensure adherence of a research output to a customized class, and the ability to register a custom class to our schema registry enabling others to search and re-use it. We demonstrate the use of our tool with the creation of the Outbreak.info schema—a large multi-class schema for harmonizing various COVID-19 related resources. Conclusions: We have created a browser-based tool to empower biomedical research resource providers to leverage Schema.org classes to make their research outputs more FAIR.", + "authors": [ + { + "name": "Cano M.A." + }, + { + "name": "Hughes L.D." + }, + { + "name": "Mullen J.L." + }, + { + "name": "Su A.I." + }, + { + "name": "Tsueng G." + }, + { + "name": "Wu C." + }, + { + "name": "Xin J." + }, + { + "name": "Zhou X." + } + ], + "date": "2023-12-01T00:00:00Z", + "journal": "BMC Bioinformatics", + "title": "Schema Playground: a tool for authoring, extending, and using metadata schemas to improve FAIRness of biomedical data" + }, + "pmcid": "PMC10116472", + "pmid": "37081398", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Ontology" + ], + "topic": [ + { + "term": "Allergy, clinical immunology and immunotherapeutics", + "uri": "http://edamontology.org/topic_3400" + }, + { + "term": "Infectious disease", + "uri": "http://edamontology.org/topic_3324" + }, + { + "term": "Ontology and terminology", + "uri": "http://edamontology.org/topic_0089" + }, + { + "term": "Plant biology", + "uri": "http://edamontology.org/topic_0780" + }, + { + "term": "Transcription factors and regulatory sites", + "uri": "http://edamontology.org/topic_0749" + } + ] +} diff --git a/data/scree/scree.biotools.json b/data/scree/scree.biotools.json new file mode 100644 index 0000000000000..311289c229165 --- /dev/null +++ b/data/scree/scree.biotools.json @@ -0,0 +1,105 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T18:48:23.199719Z", + "biotoolsCURIE": "biotools:scree", + "biotoolsID": "scree", + "confidence_flag": "high", + "cost": "Free of charge", + "credit": [ + { + "email": "08chenfeiwang@tongji.edu.cn", + "name": "Qiu Wu", + "typeEntity": "Person" + }, + { + "email": "qiu_wu@tongji.edu.cn", + "name": "Chenfei Wang", + "typeEntity": "Person" + } + ], + "description": "Comprehensive pipeline for single-cell multi-modal CRISPR screen data processing and analysis.", + "editPermission": { + "type": "public" + }, + "function": [ + { + "operation": [ + { + "term": "Gene expression profiling", + "uri": "http://edamontology.org/operation_0314" + }, + { + "term": "Quantification", + "uri": "http://edamontology.org/operation_3799" + }, + { + "term": "Read pre-processing", + "uri": "http://edamontology.org/operation_3219" + } + ] + } + ], + "homepage": "https://github.com/wanglabtongji/SCREE", + "language": [ + "R" + ], + "lastUpdate": "2023-10-15T18:48:23.202431Z", + "license": "GPL-3.0", + "name": "SCREE", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1093/BIB/BBAD123", + "metadata": { + "abstract": "Single-cell CRISPR screens have been widely used to investigate gene regulatory circuits in diverse biological systems. The recent development of single-cell CRISPR screens has enabled multimodal profiling of perturbed cells with both gene expression, chromatin accessibility and protein levels. However, current methods cannot meet the analysis requirements of different types of data and have limited functions. Here, we introduce Single-cell CRISPR screens data analysEs and perturbation modEling (SCREE) as a comprehensive and flexible pipeline to facilitate the analyses of various types of single-cell CRISPR screens data. SCREE performs read alignment, sgRNA assignment, quality control, clustering and visualization, perturbation enrichment evaluation, perturbation efficiency modeling, gene regulatory score calculation and functional analyses of perturbations for single-cell CRISPR screens with both RNA, ATAC and multimodal readout. SCREE is available at https://github.com/wanglabtongji/SCREE.", + "authors": [ + { + "name": "Han T." + }, + { + "name": "Li T." + }, + { + "name": "Wang C." + }, + { + "name": "Wei H." + }, + { + "name": "Wu Q." + } + ], + "citationCount": 1, + "date": "2023-05-01T00:00:00Z", + "journal": "Briefings in Bioinformatics", + "title": "SCREE: a comprehensive pipeline for single-cell multi-modal CRISPR screen data processing and analysis" + }, + "pmid": "37000175", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Workflow" + ], + "topic": [ + { + "term": "Gene expression", + "uri": "http://edamontology.org/topic_0203" + }, + { + "term": "Molecular interactions, pathways and networks", + "uri": "http://edamontology.org/topic_0602" + }, + { + "term": "Workflows", + "uri": "http://edamontology.org/topic_0769" + } + ] +} diff --git a/data/springer/springer.biotools.json b/data/springer/springer.biotools.json new file mode 100644 index 0000000000000..83f6058cb01e5 --- /dev/null +++ b/data/springer/springer.biotools.json @@ -0,0 +1,85 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T19:39:45.350195Z", + "biotoolsCURIE": "biotools:springer", + "biotoolsID": "springer", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "wucen@ksu.edu", + "name": "Cen Wu", + "typeEntity": "Person" + } + ], + "description": "An R package for bi-level variable selection of high-dimensional longitudinal data.", + "editPermission": { + "type": "public" + }, + "function": [ + { + "operation": [ + { + "term": "Feature selection", + "uri": "http://edamontology.org/operation_3936" + }, + { + "term": "Genotyping", + "uri": "http://edamontology.org/operation_3196" + }, + { + "term": "Regression analysis", + "uri": "http://edamontology.org/operation_3659" + } + ] + } + ], + "homepage": "https://cran.r-project.org/package=springer", + "language": [ + "R" + ], + "lastUpdate": "2023-10-15T19:39:45.352886Z", + "license": "GPL-2.0", + "link": [ + { + "type": [ + "Repository" + ], + "url": "https://github.com/feizhoustat/springer" + } + ], + "name": "springer", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.3389/FGENE.2023.1088223", + "pmcid": "PMC10117642", + "pmid": "37091810", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Library" + ], + "topic": [ + { + "term": "Genetics", + "uri": "http://edamontology.org/topic_3053" + }, + { + "term": "Literature and language", + "uri": "http://edamontology.org/topic_3068" + }, + { + "term": "Molecular interactions, pathways and networks", + "uri": "http://edamontology.org/topic_0602" + } + ] +} diff --git a/data/streammd/streammd.biotools.json b/data/streammd/streammd.biotools.json new file mode 100644 index 0000000000000..7656e3aa20df4 --- /dev/null +++ b/data/streammd/streammd.biotools.json @@ -0,0 +1,113 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-15T17:43:14.874562Z", + "biotoolsCURIE": "biotools:streammd", + "biotoolsID": "streammd", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "conrad.leonard@qimrberghofer.edu.au", + "name": "Conrad Leonard", + "orcidid": "https://orcid.org/0000-0002-4131-2065", + "typeEntity": "Person" + } + ], + "description": "Fast low-memory duplicate marking using a Bloom filter.", + "editPermission": { + "type": "private" + }, + "function": [ + { + "input": [ + { + "data": { + "term": "Sequence alignment", + "uri": "http://edamontology.org/data_0863" + }, + "format": [ + { + "term": "SAM", + "uri": "http://edamontology.org/format_2573" + } + ] + } + ], + "operation": [ + { + "term": "Duplication detection", + "uri": "http://edamontology.org/operation_3963" + }, + { + "term": "Filtering", + "uri": "http://edamontology.org/operation_3695" + } + ], + "output": [ + { + "data": { + "term": "Sequence attribute", + "uri": "http://edamontology.org/data_2534" + }, + "format": [ + { + "term": "SAM", + "uri": "http://edamontology.org/format_2573" + } + ] + } + ] + } + ], + "homepage": "https://github.com/delocalizer/streammd", + "language": [ + "C++" + ], + "lastUpdate": "2023-10-15T17:43:14.877034Z", + "license": "MIT", + "name": "streammd", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1093/BIOINFORMATICS/BTAD181", + "metadata": { + "abstract": "Summary: Identification of duplicate templates is a common preprocessing step in bulk sequence analysis; for large libraries, this can be resource intensive. Here, we present streammd: a fast, memory-efficient, single-pass duplicate marker operating on the principle of a Bloom filter. streammd closely reproduces outputs from Picard MarkDuplicates while being substantially faster, and requires much less memory than SAMBLASTER. Availability and implementation: streammd is a C＋＋ program available from GitHub https://github.com/delocalizer/ streammd under the MIT license.", + "authors": [ + { + "name": "Leonard C." + } + ], + "date": "2023-04-01T00:00:00Z", + "journal": "Bioinformatics", + "title": "streammd: fast low-memory duplicate marking using a Bloom filter" + }, + "pmcid": "PMC10112951", + "pmid": "37027230", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Command-line tool" + ], + "topic": [ + { + "term": "Mapping", + "uri": "http://edamontology.org/topic_0102" + }, + { + "term": "Whole genome sequencing", + "uri": "http://edamontology.org/topic_3673" + }, + { + "term": "Workflows", + "uri": "http://edamontology.org/topic_0769" + } + ] +} diff --git a/data/svsearcher/svsearcher.biotools.json b/data/svsearcher/svsearcher.biotools.json new file mode 100644 index 0000000000000..3cf4fbc420985 --- /dev/null +++ b/data/svsearcher/svsearcher.biotools.json @@ -0,0 +1,108 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-17T13:36:00.637862Z", + "biotoolsCURIE": "biotools:svsearcher", + "biotoolsID": "svsearcher", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "kwksung@cuhk.edu.hk", + "name": "Wing-Kin Sung" + } + ], + "description": "A more accurate structural variation detection method in long read data.", + "editPermission": { + "type": "private" + }, + "function": [ + { + "input": [ + { + "data": { + "term": "Nucleic acid sequence", + "uri": "http://edamontology.org/data_2977" + }, + "format": [ + { + "term": "FASTA", + "uri": "http://edamontology.org/format_1929" + } + ] + }, + { + "data": { + "term": "Nucleic acid sequence alignment", + "uri": "http://edamontology.org/data_1383" + }, + "format": [ + { + "term": "BAM", + "uri": "http://edamontology.org/format_2572" + } + ] + } + ], + "operation": [ + { + "term": "Information extraction", + "uri": "http://edamontology.org/operation_3907" + }, + { + "term": "Read mapping", + "uri": "http://edamontology.org/operation_3198" + }, + { + "term": "Structural variation detection", + "uri": "http://edamontology.org/operation_3228" + } + ], + "output": [ + { + "data": { + "term": "Sequence variations", + "uri": "http://edamontology.org/data_3498" + } + } + ] + } + ], + "homepage": "https://github.com/kensung-lab/SVsearcher", + "language": [ + "Python" + ], + "lastUpdate": "2023-10-17T13:36:00.640456Z", + "name": "SVsearcher", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1016/J.COMPBIOMED.2023.106843", + "pmid": "37019014", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Command-line tool" + ], + "topic": [ + { + "term": "Evolutionary biology", + "uri": "http://edamontology.org/topic_3299" + }, + { + "term": "Sequence analysis", + "uri": "http://edamontology.org/topic_0080" + }, + { + "term": "Structural variation", + "uri": "http://edamontology.org/topic_3175" + } + ] +} diff --git a/data/transxpress/transxpress.biotools.json b/data/transxpress/transxpress.biotools.json new file mode 100644 index 0000000000000..487abbc703458 --- /dev/null +++ b/data/transxpress/transxpress.biotools.json @@ -0,0 +1,122 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-16T14:05:56.455518Z", + "biotoolsCURIE": "biotools:transxpress", + "biotoolsID": "transxpress", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "tomas.pluskal@uochb.cas.cz", + "name": "Tomáš Pluskal", + "orcidid": "https://orcid.org/0000-0002-6940-3006", + "typeEntity": "Person" + }, + { + "email": "wengj@wi.mit.edu", + "name": "Jing-Ke Weng", + "typeEntity": "Person" + } + ], + "description": "Snakemake pipeline for streamlined de novo transcriptome assembly and annotation.", + "editPermission": { + "type": "private" + }, + "function": [ + { + "operation": [ + { + "term": "De-novo assembly", + "uri": "http://edamontology.org/operation_0524" + }, + { + "term": "Differential gene expression profiling", + "uri": "http://edamontology.org/operation_3223" + }, + { + "term": "RNA-Seq quantification", + "uri": "http://edamontology.org/operation_3800" + }, + { + "term": "Transcriptome assembly", + "uri": "http://edamontology.org/operation_3258" + }, + { + "term": "k-mer counting", + "uri": "http://edamontology.org/operation_3472" + } + ] + } + ], + "homepage": "https://github.com/transXpress/transXpress", + "language": [ + "Bash", + "Python" + ], + "lastUpdate": "2023-10-16T14:05:56.458498Z", + "license": "GPL-3.0", + "name": "transXpress", + "operatingSystem": [ + "Linux" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1186/S12859-023-05254-8", + "metadata": { + "abstract": "Background: RNA-seq followed by de novo transcriptome assembly has been a transformative technique in biological research of non-model organisms, but the computational processing of RNA-seq data entails many different software tools. The complexity of these de novo transcriptomics workflows therefore presents a major barrier for researchers to adopt best-practice methods and up-to-date versions of software. Results: Here we present a streamlined and universal de novo transcriptome assembly and annotation pipeline, transXpress, implemented in Snakemake. transXpress supports two popular assembly programs, Trinity and rnaSPAdes, and allows parallel execution on heterogeneous cluster computing hardware. Conclusions: transXpress simplifies the use of best-practice methods and up-to-date software for de novo transcriptome assembly, and produces standardized output files that can be mined using SequenceServer to facilitate rapid discovery of new genes and proteins in non-model organisms.", + "authors": [ + { + "name": "Calounova T." + }, + { + "name": "Fallon T.R." + }, + { + "name": "Mokrejs M." + }, + { + "name": "Pluskal T." + }, + { + "name": "Weng J.-K." + } + ], + "citationCount": 1, + "date": "2023-12-01T00:00:00Z", + "journal": "BMC Bioinformatics", + "title": "transXpress: a Snakemake pipeline for streamlined de novo transcriptome assembly and annotation" + }, + "pmcid": "PMC10074830", + "pmid": "37016291", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Workflow" + ], + "topic": [ + { + "term": "Computer science", + "uri": "http://edamontology.org/topic_3316" + }, + { + "term": "RNA-Seq", + "uri": "http://edamontology.org/topic_3170" + }, + { + "term": "Sequence assembly", + "uri": "http://edamontology.org/topic_0196" + }, + { + "term": "Transcriptomics", + "uri": "http://edamontology.org/topic_3308" + }, + { + "term": "Workflows", + "uri": "http://edamontology.org/topic_0769" + } + ] +} diff --git a/data/twas_sim/twas_sim.biotools.json b/data/twas_sim/twas_sim.biotools.json new file mode 100644 index 0000000000000..aab8097fb873b --- /dev/null +++ b/data/twas_sim/twas_sim.biotools.json @@ -0,0 +1,115 @@ +{ + "additionDate": "2023-10-15T19:53:22.458869Z", + "biotoolsCURIE": "biotools:twas_sim", + "biotoolsID": "twas_sim", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "nmancuso@usc.edu", + "name": "Nicholas Mancuso", + "orcidid": "https://orcid.org/0000-0002-9352-5927", + "typeEntity": "Person" + }, + { + "email": "xwang505@usc.edu", + "name": "Xinran Wang", + "orcidid": "https://orcid.org/0000-0001-9670-3939", + "typeEntity": "Person" + } + ], + "description": "Python-based tool for simulation and power analysis of transcriptome-wide association analysis.", + "editPermission": { + "type": "private" + }, + "function": [ + { + "operation": [ + { + "term": "Genotyping", + "uri": "http://edamontology.org/operation_3196" + }, + { + "term": "Quantification", + "uri": "http://edamontology.org/operation_3799" + }, + { + "term": "Simulation analysis", + "uri": "http://edamontology.org/operation_0244" + } + ] + } + ], + "homepage": "https://github.com/mancusolab/twas_sim", + "language": [ + "Python", + "R", + "Shell" + ], + "lastUpdate": "2023-10-15T19:53:22.461568Z", + "name": "twas_sim", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1093/BIOINFORMATICS/BTAD288", + "metadata": { + "abstract": "Genome-wide association studies (GWASs) have identified numerous genetic variants associated with complex disease risk; however, most of these associations are non-coding, complicating identifying their proximal target gene. Transcriptome-wide association studies (TWASs) have been proposed to mitigate this gap by integrating expression quantitative trait loci (eQTL) data with GWAS data. Numerous methodological advancements have been made for TWAS, yet each approach requires ad hoc simulations to demonstrate feasibility. Here, we present twas_sim, a computationally scalable and easily extendable tool for simplified performance evaluation and power analysis for TWAS methods.", + "authors": [ + { + "name": "Bhattacharya A." + }, + { + "name": "Lu Z." + }, + { + "name": "Mancuso N." + }, + { + "name": "Pasaniuc B." + }, + { + "name": "Wang X." + } + ], + "date": "2023-05-01T00:00:00Z", + "journal": "Bioinformatics", + "title": "twas_sim, a Python-based tool for simulation and power analysis of transcriptome-wide association analysis" + }, + "pmcid": "PMC10172036", + "pmid": "37099718", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Command-line tool" + ], + "topic": [ + { + "term": "DNA polymorphism", + "uri": "http://edamontology.org/topic_2885" + }, + { + "term": "GWAS study", + "uri": "http://edamontology.org/topic_3517" + }, + { + "term": "Gene expression", + "uri": "http://edamontology.org/topic_0203" + }, + { + "term": "Genotype and phenotype", + "uri": "http://edamontology.org/topic_0625" + }, + { + "term": "Mapping", + "uri": "http://edamontology.org/topic_0102" + } + ] +} diff --git a/data/ukb_db/ukb_db.biotools.json b/data/ukb_db/ukb_db.biotools.json new file mode 100644 index 0000000000000..76b000f8467bf --- /dev/null +++ b/data/ukb_db/ukb_db.biotools.json @@ -0,0 +1,116 @@ +{ + "accessibility": "Open access", + "additionDate": "2023-10-16T14:56:22.237230Z", + "biotoolsCURIE": "biotools:ukb_db", + "biotoolsID": "ukb_db", + "confidence_flag": "tool", + "cost": "Free of charge", + "credit": [ + { + "email": "king.jordan@biology.gatech.edu", + "name": "I King Jordan", + "orcidid": "https://orcid.org/0000-0003-4996-2203", + "typeEntity": "Person" + }, + { + "email": "marino@nih.gov", + "name": "Leonardo Mariño-Ramírez", + "orcidid": "https://orcid.org/0000-0002-5716-8512", + "typeEntity": "Person" + } + ], + "description": "The landscape of health disparities in the UK Biobank.", + "editPermission": { + "type": "private" + }, + "function": [ + { + "operation": [ + { + "term": "Aggregation", + "uri": "http://edamontology.org/operation_3436" + }, + { + "term": "Database search", + "uri": "http://edamontology.org/operation_2421" + }, + { + "term": "Sorting", + "uri": "http://edamontology.org/operation_3802" + } + ] + } + ], + "homepage": "https://ukbatlas.health-disparities.org", + "language": [ + "Python" + ], + "lastUpdate": "2023-10-16T14:56:22.240015Z", + "link": [ + { + "type": [ + "Repository" + ], + "url": "https://github.com/healthdisparities/UKB-Disparity-Atlas" + } + ], + "name": "UKB", + "operatingSystem": [ + "Linux", + "Mac", + "Windows" + ], + "owner": "Pub2Tools", + "publication": [ + { + "doi": "10.1093/DATABASE/BAAD026", + "metadata": { + "abstract": "The UK Biobank (UKB), a large-scale biomedical database that includes demographic and electronic health record data for more than half a million ethnically diverse participants, is a potentially valuable resource for the study of health disparities. However, publicly accessible databases that catalog health disparities in the UKB do not exist. We developed the UKB Health Disparities Browser with the aims of (i) facilitating the exploration of the landscape of health disparities in the UK and (ii) directing the attention to areas of disparities research that might have the greatest public health impact. Health disparities were characterized for UKB participant groups defined by age, country of residence, ethnic group, sex and socioeconomic deprivation. We defined disease cohorts for UKB participants by mapping participant International Classification of Diseases, Tenth Revision (ICD-10) diagnosis codes to phenotype codes (phecodes). For each of the population attributes used to define population groups, disease percent prevalence values were computed for all groups from phecode case-control cohorts, and the magnitude of the disparities was calculated by both the difference and ratio of the range of disease prevalence values among groups to identify high- and low-prevalence disparities. We identified numerous diseases and health conditions with disparate prevalence values across population attributes, and we deployed an interactive web browser to visualize the results of our analysis: https://ukbatlas.health-disparities.org. The interactive browser includes overall and group-specific prevalence data for 1513 diseases based on a cohort of >500 000 participants from the UKB. Researchers can browse and sort by disease prevalence and prevalence differences to visualize health disparities for each of the five population attributes, and users can search for diseases of interest by disease names or codes. Database URL https://ukbatlas.health-disparities.org/", + "authors": [ + { + "name": "Jordan I.K." + }, + { + "name": "Marino-Ramirez L." + }, + { + "name": "Nagar S.D." + } + ], + "date": "2023-01-01T00:00:00Z", + "journal": "Database", + "title": "The landscape of health disparities in the UK Biobank" + }, + "pmcid": "PMC10132819", + "pmid": "37114803", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Database portal" + ], + "topic": [ + { + "term": "Allergy, clinical immunology and immunotherapeutics", + "uri": "http://edamontology.org/topic_3400" + }, + { + "term": "Biobank", + "uri": "http://edamontology.org/topic_3337" + }, + { + "term": "Medical informatics", + "uri": "http://edamontology.org/topic_3063" + }, + { + "term": "Pathology", + "uri": "http://edamontology.org/topic_0634" + }, + { + "term": "Public health and epidemiology", + "uri": "http://edamontology.org/topic_3305" + } + ] +} diff --git a/data/ular_toto/ular_toto.biotools.json b/data/ular_toto/ular_toto.biotools.json deleted file mode 100644 index d5ca8ac36a31c..0000000000000 --- a/data/ular_toto/ular_toto.biotools.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "additionDate": "2023-10-12T12:12:52.620016Z", - "biotoolsCURIE": "biotools:ular_toto", - "biotoolsID": "ular_toto", - "description": "Ulartoto terpercaya merupakan situs yang sudah berlisensi resmi. 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However, the conventional process of model buildings can be complex and time consuming due to challenges such as peptide representation, feature selection, model selection and hyperparameter tuning. Recently, advanced pretrained deep learning-based language models (LMs) have been released for protein sequence embedding and applied to structure and function prediction. Based on these developments, we have developed UniDL4BioPep, a universal deep-learning model architecture for transfer learning in bioactive peptide binary classification modeling. It can directly assist users in training a high-performance deep-learning model with a fixed architecture and achieve cutting-edge performance to meet the demands in efficiently novel bioactive peptide discovery. To the best of our best knowledge, this is the first time that a pretrained biological language model is utilized for peptide embeddings and successfully predicts peptide bioactivities through large-scale evaluations of those peptide embeddings. The model was also validated through uniform manifold approximation and projection analysis. By combining the LM with a convolutional neural network, UniDL4BioPep achieved greater performances than the respective state-of-the-art models for 15 out of 20 different bioactivity dataset prediction tasks. The accuracy, Mathews correlation coefficient and area under the curve were 0.7-7, 1.23-26.7 and 0.3-25.6% higher, respectively. A user-friendly web server of UniDL4BioPep for the tested bioactivities is established and freely accessible at https://nepc2pvmzy.us-east-1.awsapprunner.com. The source codes, datasets and templates of UniDL4BioPep for other bioactivity fitting and prediction tasks are available at https://github.com/dzjxzyd/UniDL4BioPep.", + "authors": [ + { + "name": "Ding X." + }, + { + "name": "Du Z." + }, + { + "name": "Li Y." + }, + { + "name": "Xu Y." + } + ], + "citationCount": 5, + "date": "2023-05-01T00:00:00Z", + "journal": "Briefings in Bioinformatics", + "title": "UniDL4BioPep: a universal deep learning architecture for binary classification in peptide bioactivity" + }, + "pmid": "37020337", + "type": [ + "Primary" + ] + } + ], + "toolType": [ + "Web application" + ], + "topic": [ + { + "term": "Gene and protein families", + "uri": "http://edamontology.org/topic_0623" + }, + { + "term": "Machine learning", + "uri": "http://edamontology.org/topic_3474" + }, + { + "term": "Proteomics", + "uri": "http://edamontology.org/topic_0121" + }, + { + "term": "Small molecules", + "uri": "http://edamontology.org/topic_0154" + } + ] +} diff --git a/data/veryfasttree/veryfasttree.biotools.json b/data/veryfasttree/veryfasttree.biotools.json index 57b3232d608c9..10dfc9452969d 100644 --- a/data/veryfasttree/veryfasttree.biotools.json +++ b/data/veryfasttree/veryfasttree.biotools.json @@ -5,6 +5,24 @@ "biotoolsID": "veryfasttree", "cost": "Free of charge", "description": "VeryFastTree is a highly-tuned implementation of the FastTree-2 tool that takes advantage of parallelization and vectorization strategies to speed up the inference of phylogenies for huge alignments. It is important to highlight that VeryFastTree keeps unchanged the phases, methods and heuristics used by FastTree-2 to estimate the phylogenetic tree. In this way, it produces trees with the same topological accuracy than FastTree-2. In addition, unlike the parallel version of FastTree-2, VeryFastTree is deterministic.\n\nTo facilitate the adoption from the research community, VeryFastTree keeps exactly the same command line arguments than FastTree-2. In this way, it is only necessary to replace the call to FastTree-2 by a call to VeryFastTree using the same options to increase the overall performance.", + "download": [ + { + "note": "bioconda package", + "type": "Software package", + "url": "https://anaconda.org/bioconda/veryfasttree" + }, + { + "note": "packaging status", + "type": "Software package", + "url": "https://repology.org/badge/vertical-allrepos/veryfasttree.svg" + }, + { + "note": "github releases", + "type": "Downloads page", + "url": "https://github.com/citiususc/veryfasttree/releases/latest", + "version": "latest" + } + ], "editPermission": { "type": "private" }, @@ -60,7 +78,7 @@ "language": [ "C++" ], - "lastUpdate": "2023-05-22T15:46:34.137149Z", + "lastUpdate": "2023-10-17T15:25:45.517066Z", "license": "GPL-3.0", "maturity": "Mature", "name": "VeryFastTree", @@ -86,7 +104,7 @@ "name": "Pineiro C." } ], - "citationCount": 8, + "citationCount": 10, "date": "2020-09-01T00:00:00Z", "journal": "Bioinformatics", "title": "Very fast tree: Speeding up the estimation of phylogenies for large alignments through parallelization and vectorization strategies" @@ -113,6 +131,9 @@ "3.1.1", "3.2.0", "3.2.1", - "4.0(dev)" + "4.0", + "4.0.1", + "4.0.2", + "4.0.3" ] }