Update README.md

README.md

@@ -10,16 +10,16 @@
 [![downloads](https://anaconda.org/kalininalab/datasail/badges/downloads.svg)](https://anaconda.org/kalininalab/datasail)
 ![Python 3](https://img.shields.io/badge/python-3-blue.svg)
 
-DataSAIL is a tool that splits data while minimizing the information leakage. This tool formulates the splitting of a 
-dataset as constrained minimization problem and computes the assignment of data points to splits while minimizing the 
+DataSAIL is a tool that splits data while minimizing Information Leakage. This tool formulates the splitting of a 
+dataset as a constrained minimization problem and computes the assignment of data points to splits while minimizing the 
 objective function that accounts for information leakage.
 
 Internally, DataSAIL uses disciplined quasi-convex programming and binary quadratic programs to formulate the 
 optimization task. DataSAIL utilizes solves like [SCIP](https://scipopt.org/), one of the fastest non-commercial 
-solvers for this type of problems, and [MOSEK](https://mosek.com), a commercial solver that distributes free licenses 
-for academic use. There are other options, please check the documentation.
+solvers for this type of problem, and [MOSEK](https://mosek.com), a commercial solver that distributes free licenses 
+for academic use. There are other options; please check the documentation.
 
-Apart from the here presented short overview, you can find a more detailed explanation of the tool on 
+Apart from the short overview, you can find a more detailed explanation of the tool on 
 [ReadTheDocs](https://datasail.readthedocs.io/en/latest/index.html). 
 
 ## Installation
@@ -37,7 +37,7 @@ pip install grakel
 to install it into a new empty environment or
 
 ````shell
-conda install -c conda-forge -c kalininalab -c bioconda -c mosek DataSAIL
+mamba install -c conda-forge -c kalininalab -c bioconda -c mosek DataSAIL
 pip install grakel
 ````
 
@@ -48,23 +48,23 @@ DataSAIL is available from Python 3.8 and newer.
 
 ## Usage
 
-DataSAIL is installed as a commandline tool. So, in the conda environment DataSAIL has been installed to, you can run 
+DataSAIL is installed as a command-line tool. So, in the conda environment, DataSAIL has been installed to, you can run 
 
 ````shell
 datasail --e-type P --e-data <path_to_fasta> --e-sim mmseqs --output <path_to_output_path> --technique C1e
 ````
 
-to split a set of proteins that have been clustered using mmseqs. For a full list of arguments run `datasail -h` and 
+to split a set of proteins that have been clustered using mmseqs. For a full list of arguments, run `datasail -h` and 
 checkout [ReadTheDocs](https://datasail.readthedocs.io/en/latest/index.html).
 
 ## When to use DataSAIL and when not to use
 
-One can distinguish two main ways to train a machine learning model on biological data. 
-* Either the model shall be applied to data that is substantially different from the data to train on. In this case it 
-  is important to have test cases that model this real world application scenario properly by being as dissimilar as 
+One can distinguish two main ways to train a machine-learning model on biological data. 
+* Either the model shall be applied to data substantially different from the data to train on. In this case, it 
+  is essential to have test cases that correctly model this real-world application scenario by being as dissimilar as 
   possible to the training data. 
-* Or the training dataset already covers the full space of possible samples shown to the model.
+* Or the training dataset already covers the whole space of possible samples shown to the model.
 
-DataSAIL is created to compute complex splits of the data by separating data based on similarities. This creates 
-complex data-splits for the first scenario. Therefore, use DataSAIL when your model is applied to data that is 
-different from your training data but not if the data in application is more or less the same as in the training.
+DataSAIL is created to compute complex data splits by separating data based on similarities. This makes 
+complex data splits for the first scenario. So, you can use DataSAIL when your model is applied to data  
+different from your training data but not if the data in the application is more or less the same as in the training.