# MMADPE_LMX

**Repository Path**: Tomhappy/MMADPE_LMX

## Basic Information

- **Project Name**: MMADPE_LMX
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2026-04-11
- **Last Updated**: 2026-04-11

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

MMADPE: Drug Repositioning Based on Multi-hop Graph Mamba Aggregation with Dual-modality Graph Positional Encoding
Requirements:

    python 3.9.19
    pandas 2.0.3
    cudatoolkit 11.3.1
    pytorch 2.3.0
    numpy 1.23.5
    scikit-learn 1.2.2

Data:

The data files needed to run the model, which contain C-dataset and F-dataset.

    DrugFingerprint, DrugGIP: The similarity measurements of drugs to construct the similarity network
    DiseasePS, DiseaseGIP: The similarity measurements of diseases to construct the similarity network
    DrugDiseaseAssociationNumber: The known drug disease associations
    DiseaseFeature: The features of diseases
    Drug_mol2vec: The features of drugs

Code:

    utils.py: Methods of data processing
    metric.py: Metrics calculation
    train_DDA.py: Train the model

Installation method for the torch_geometric series (install in order):
# pip install torch-scatter -f https://pytorch-geometric.com/whl/torch-2.3.0+cu121.html
# pip install torch-sparse -f https://pytorch-geometric.com/whl/torch-2.3.0+cu121.html
# pip install torch-cluster -f https://pytorch-geometric.com/whl/torch-2.3.0+cu121.html
# pip install torch-spline-conv -f https://pytorch-geometric.com/whl/torch-2.3.0+cu121.html
# pip install torch-geometric

Usage:

Execute python main.py