# GCFMCL1

**Repository Path**: Tomhappy/gcfmcl1

## Basic Information

- **Project Name**: GCFMCL1
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2026-09-03
- **Last Updated**: 2026-09-03

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# GCFMCL: Predicting miRNA–Drug Sensitivity Using Graph Collaborative Filtering and Multi-View Contrastive Learning

This repository contains the official implementation of the paper:

> **GCFMCL: predicting miRNA–drug sensitivity using graph collaborative filtering and multi-view contrastive learning**
> **Jinhang Wei**, Linlin Zhuo, Zhecheng Zhou, Xinze Lian, Xiangzheng Fu, Xiaojun Yao.
> *Briefings in Bioinformatics*, 2023.
> DOI: [10.1093/bib/bbad247](https://doi.org/10.1093/bib/bbad247)

> **Note on authorship:** This code repository was primarily developed by **Jinhang Wei** (first author).

## requirements:

recbole : 1.1.1

pytorch : 1.13.1(Any major version)

numpy : 1.20.3(Any major version)

pandas : 1.5.2(Any major version)

matplotlib : 3.7.1(Any major version)

scipy : 1.93

faiss : 1.7.2 (Please use 'conda install faiss')

#Notice:You can use pip install -r "requirements.txt" and then use conda install faiss to complete the environment setup.

How to run:

Just open main.py and run it, no configuration required.