GNNGL_PPI

Codes and models for the paper "GNNGL-PPI: Multi-category Prediction of Protein-Protein Interactions using Graph Neural Networks based on Global Graphs and Local Subgraphs".

Using GNNGL_PPI

This repository contains:

• Requirements
• Data Processing
• Training
• Testing

Requirements

(1) python 3.7
(2) torch-1.10.2+cu113
(3) torchaudio-0.10.2
(4) torchvision-0.11.3+cu113
(5) dgl-1.0.2+cu113
(6) cudatoolkit-10.1.168
(7) numpy-1.19.5
(8) pandas
(9) scikit-learn-0.22.2

Data Processing

The data processing codes in gnn_data.py (Class GNN_DATA), including:

• data reading (def __init__)
• protein vectorize (def get_feature_pretrain)
• generate pyg data (def generate_data)
• Data partition (def split_dataset)
  • For the first time, you need to set the parameter random_new=True to generate a new data set division json file. (Otherwise, an error will be reported, No such file or directory: "./xxxx/string.bfs.fold1.json")

Training

Training codes in gnn_train.py, and the run script in run.py.

Dataset Download:

SHS27k and SHS148k:

• http://yellowstone.cs.ucla.edu/~muhao/pipr/SHS_ppi_beta.zip

This repositorie uses the processed dataset download path:

• https://pan.baidu.com/s/1FU-Ij3LxyP9dOHZxO3Aclw (Extraction code: tibn)