https://github.com/westlake-ai/openbioseq
This repo focuses on supervised and self-supervised bio-sequence representation learning
https://github.com/westlake-ai/openbioseq
bio-sequences classification-regression genetic-engineering pytorch self-supervised transformer
Last synced: about 1 month ago
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This repo focuses on supervised and self-supervised bio-sequence representation learning
- Host: GitHub
- URL: https://github.com/westlake-ai/openbioseq
- Owner: Westlake-AI
- License: apache-2.0
- Created: 2022-05-24T09:16:26.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2023-10-11T21:04:22.000Z (over 1 year ago)
- Last Synced: 2025-04-23T23:06:56.459Z (about 2 months ago)
- Topics: bio-sequences, classification-regression, genetic-engineering, pytorch, self-supervised, transformer
- Language: Python
- Homepage: https://openbioseq.readthedocs.io/en/latest/
- Size: 625 KB
- Stars: 22
- Watchers: 1
- Forks: 1
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
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README
# OpenBioSeq
[](https://pypi.org/project/OpenBioSeq)
[](https://github.com/Westlake-AI/OpenBioSeq/blob/main/LICENSE)
[](https://github.com/Westlake-AI/OpenBioSeq/issues)
**News**
* OpenBioSeq v0.1.1 is released, which supports classification and regression tasks on bio-sequence datasets. It inherited most features in [OpenMixup](https://github.com/Westlake-AI/openmixup).
* OpenBioSeq v0.1.0 is initialized.
## Introduction
The main branch works with **PyTorch 1.8** (required by some self-supervised methods) or higher (we recommend **PyTorch 1.12**). You can still use **PyTorch 1.6** for most methods.
`OpenBioSeq` is an open-source supervised and self-supervised bio-sequence representation learning toolbox based on PyTorch. `OpenBioSeq` supports popular backbones, pre-training methods, and various features.
### What does this repo do?
Learning useful bio-sequence representation efficiently facilitates various downstream tasks in biological and chemical fields. This repo focuses on supervised and self-supervised bio-sequence representation learning and is named `OpenBioSeq`.
### Major features
This repo will be continued to update in 2022! Please watch us for latest update!
## Change Log
Please refer to [CHANGELOG.md](docs/CHANGELOG.md) for details and release history.
[2022-06-09] `OpenBioSeq` v0.1.1 is released.
[2022-05-24] `OpenBioSeq` v0.1.0 is initialized.
## Installation
There are quick installation steps for develepment:
```shell
conda create -n openbioseq python=3.8 -y
conda activate openbioseq
pip install torch==1.11.0+cu113 torchvision==0.12.0+cu113 torchaudio==0.11.0 --extra-index-url https://download.pytorch.org/whl/cu113 # as an example
pip install openmim
mim install mmcv-full
git clone https://github.com/Westlake-AI/OpenBioSeq.git
cd OpenBioSeq
python setup.py develop
```
Please refer to [INSTALL.md](docs/INSTALL.md) for detailed installation instructions and dataset preparation.
## Get Started
Please see [Getting Started](docs/GETTING_STARTED.md) for the basic usage of OpenBioSeq (based on OpenMixup and MMSelfSup). As an example, you can start a multiple GPUs training with a certain `CONFIG_FILE` using the following script:
```shell
bash tools/dist_train.sh ${CONFIG_FILE} ${GPUS} [optional arguments]
```
Then, please see [tutorials](docs/tutorials) for more tech details (based on MMClassification).
## License
This project is released under the [Apache 2.0 license](LICENSE).
## Acknowledgement
- `OpenBioSeq` is an open-source project for supervised and self-supervised methods on bio-sequence datasets created by researchers in CAIRI AI LAB. We encourage researchers interested in bio-sequence research and applications to contribute to `OpenBioSeq`!
- This repo is mainly based on [OpenMixup](https://github.com/Westlake-AI/openmixup), and borrows the architecture design and part of the code from [MMSelfSup](https://github.com/open-mmlab/mmselfsup) and [MMClassification](https://github.com/open-mmlab/mmclassification).
## Citation
If you find this project useful in your research, please consider cite:
```BibTeX
@misc{2022openbioseq,
title={{OpenBioSeq}: Open Toolbox and Benchmark for Bio-sequence Representation Learning},
author={Li, Siyuan and Liu, Zicheng and Wu, Di and Stan Z. Li},
howpublished = {\url{https://github.com/Westlake-AI/openbioseq}},
year={2022}
}
```
## Contributors
For now, the direct contributors include: Siyuan Li ([@Lupin1998](https://github.com/Lupin1998)) and Zicheng Liu ([@pone7](https://github.com/pone7)). We thanks contributors for OpenMixup, MMSelfSup, and MMClassification.
## Contact
This repo is currently maintained by Siyuan Li ([email protected]) and Zicheng Liu ([email protected]).