iDMer: an integrative and Mechanism-driven response system for identifying compound interventions for sudden virus outbreak

iDMer is an integrative and Mechanism-driven response system for addressing sudden virus outbreaks. The basic idea of iDMer is to identify compound interventions for any virus for which the genome is sequenced. It comprises 3 mechanism-driven compound identification modules, i.e. a virus-host interaction-oriented module, an autophagy-oriented module, and a cytokine release syndrome-oriented module. Further, as a one-stop integrative platform, iDMer incorporates compound toxicity evaluation and compound combination identification for virus treatment with clear mechanisms.

Authors:

Zhiting Wei, Yuli Gao and Fangliangzi Meng and Qi Liu

Citation:

iDMer: an integrative Data and Mechanism-driven epidemic response system for identifying compound interventions for sudden virus outbreak, submitted, 2020.

Dependencies

Required Software:

• dgl
• pytorch
• scikit-learn
• miniconda2
• miniconda3
• cmapPy
• deepDDI
• ProTox-II
• HVPPI
• biopython

Installation

Install via docker, highly recommended

Docker image of iDMer is available at https://hub.docker.com/r/bm2lab/idmer/. if you have docker installed, you can pull the image:

    docker pull bm2lab/idmer

Install from source, not recommended.

Please download the deepDDI and HVPPI tool, and place run_DeepDDI.py and doc2vec_rf.py in the corresponding directory.

    git clone https://github.com/bm2-lab/iDMer.git

Usage

iDMer has two modes for use, i.e., exp and denovo mode.

You can use these two mode by:

    python main.py exp --help

or

    python main.py denovo --help

User Manual

For detailed information about usage, input and output files, test examples and data preparation, please refer to the iDMer User Manual

Contact

Zhiting Wei [email protected]
Qi Liu [email protected]
Tongji University, Shanghai, China

iDMer flowchart