# transformerCPI

**Repository Path**: zhangshirui1/transformerCPI

## Basic Information

- **Project Name**: transformerCPI
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-07-25
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# TransformerCPI: Improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments

This repository contains the source code and the data.

## TransformerCPI

![](model.png)



## Setup and dependencies 

Dependencies:
- python 3.6
- pytorch >= 1.2.0
- numpy
- RDkit = 2019.03.3.0
- pandas
- Gensim >=3.4.0

## Data sets

The data sets with train/test splits are provided as .7z file in a directory called 'data'. 

The test set is created specially for label reversal experiments.

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## Using

1.`mol_featurizer.py` generates input for TransformerCPI model.

2.`main.py` trains TransformerCPI model.

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## Author

Lifan Chen (s18-chenlifan@simm.ac.cn)

Mingyue Zheng（myzheng@simm.ac.cn)

## Citation

Lifan Chen, Xiaoqin Tan, Dingyan Wang, Feisheng Zhong, Xiaohong Liu, Tianbiao Yang, Xiaomin Luo, Kaixian Chen, Hualiang Jiang, Mingyue Zheng, TransformerCPI: Improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments, Bioinformatics, , btaa524, https://doi.org/10.1093/bioinformatics/btaa524