awesome-ai-bioinformatics

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awesome-ai-bioinformatics

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A curated list of awesome AI and Bioinformatics.

awesome-ai-bioinformatics 최신버젼 다운로드

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![image](https://raw.githubusercontent.com/HongxinXiang/awesome-ai-bioinformatics/master/asset/logo.png)
[![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/HongxinXiang/awesome-ai-bioinformatics)
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This project aims to summarize the awesome research progress of AI+bioinformatics (e.g. molecules, proteins, mass spectrum, genes) from the perspective of computer science majors. Computer scientists tend to focus on data, tasks, and algorithms. Therefore, we use the logic of `data->task->algorithm` to summarize.

This repository is an ongoing project, and we welcome more collaborators to join us! If you want to become a partner, please [contact us](mailto:xianghx21@gmail.com). If you want to contribute something, please feel free to [contribute](https://github.com/HongxinXiang/awesome-ai-bioinformatics/blob/master/CONTRIBUTE.md).

# News!

**[2022/12/01]** Added new chapter "[proteins](#proteins)".

**[2022/09/22]** Added new chapter "[molecular conformation generation](#molecular-conformation-generation)".

**[2022/09/19]** Added new chapter "[conferences](#conferences)", and more latest conference papers (including NeurIPS, ICLR, AAAI, KDD, CVPR, ICML, IJCAI, etc.) in the field of AI+bioinformatics will be included.

**[2022/08/28]** Project begining.

# Table of Contents

- [tutorials](tutorials/README.md)
- single-modal learning
  - [molecules](chapters/single-modal-learning/molecules)
    - [molecular property prediction](chapters/single-modal-learning/molecules/molecular-property-prediction)
    - [molecular conformation generation](chapters/single-modal-learning/molecules/molecular-conformer-generation)
    - [molecular generation and optimization](chapters/single-modal-learning/molecules/molecular-generation-and-optimization)
    - molecular synthesis and retrosynthesis
    - drug-drug-interaction (DDI)
    - molecular docking
  - [proteins](chapters/single-modal-learning/protein/)
    - [tasks and datasets](chapters/single-modal-learning/protein)
    - [methods](chapters/single-modal-learning/protein/overview)
- multi-modal learning
- [conferences](#conferences)
  - [NeurIPS 2022](conferences/NeurIPS-2022.md)
  - [ICLR 2023](conferences/ICLR-2023.md)

# single-modal learning

## molecules

### molecular property prediction

![Alt](https://raw.githubusercontent.com/HongxinXiang/awesome-ai-bioinformatics/master/chapters/single-modal-learning/molecules/molecular-property-prediction/mindmap-mpp.png)

[Please click for more information.](chapters/single-modal-learning/molecules/molecular-property-prediction)

### molecular conformation generation

![Alt](https://raw.githubusercontent.com/HongxinXiang/awesome-ai-bioinformatics/master/chapters/single-modal-learning/molecules/molecular-conformer-generation/mindmap-mcg.png)

[Please click for more information.](chapters/single-modal-learning/molecules/molecular-conformer-generation)

### molecular generation and optimization
[Please click for more information.](chapters/single-modal-learning/molecules/molecular-generation-and-optimization)

## proteins

[Please click for more information.](chapters/single-modal-learning/protein/overview)

# multi-modal learning

# conferences

## NeurIPS 2022
[Clink this for whole list.](conferences/NeurIPS-2022.md)

# Tutorials
[Clink this for whole list.](tutorials/README.md)

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