GitHub - sshilpika/protein-graph-visualization

Visualizing Dynamically Generated Protein Interactions

A Python library for visualizing dynamically generated protein interactions using 3D node-link layout.

DEMO Video

Installation

  1. Clone the github repository

  2. Requires anaconda and python=3.8

    conda create -n myenv python=3.8
    conda activate myenv
    
  3. Install packages

    cd src/
    pip install -r requirements.txt
    

Note: You may need to install pygraphvis using conda forge: conda install --channel conda-forge pygraphviz

  1. The data file in dot file format should be stored in

  2. Start server

  3. Open browser (Google Chrome preferred)

    http://127.0.0.1:5000/index
    

Instructions to start the server

  1. Change directory to ./src

  2. Activate conda environment

  3. Start server

  4. Open browser (Google Chrome preferred)

    http://127.0.0.1:5000/index
    

References

  1. A. Vasan et al., "High Performance Binding Affinity Prediction with a Transformer-Based Surrogate Model," 2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), San Francisco, CA, USA, 2024, pp. 571-580, doi: 10.1109/IPDPSW63119.2024.00114. keywords: {Proteins;Ion radiation effects;Accuracy;Computational modeling;Pipelines;Transformers;Supercomputers;drug discovery;virtual screening;docking surrogates;high performance computing;transformers},

  2. Libraries used: D3, Flask, 3d-force-graph