AI4Protein/GO_BP_ESMFold

---
license: apache-2.0
task_categories:
- text-classification
tags:
- protein
- downstream task
---

# GO-BP Dataset with ESMFold Structural Sequence

- Description: Biological Process of Gene Ontology (GO) project.
- Number of labels: 1943
- Problem Type: multi_label_classification
- Columns:
- aa_seq: protein amino acid sequence
- foldseek_seq: foldseek 20 3di structural sequence
- ss8_seq: DSSP 8 secondary structure sequence

# Github

Simple, Efficient and Scalable Structure-aware Adapter Boosts Protein Language Models

https://github.com/tyang816/SES-Adapter

# Citation
Please cite our work if you use our dataset.
```
@article{tan2024ses-adapter,
title={Simple, Efficient, and Scalable Structure-Aware Adapter Boosts Protein Language Models},
author={Tan, Yang and Li, Mingchen and Zhou, Bingxin and Zhong, Bozitao and Zheng, Lirong and Tan, Pan and Zhou, Ziyi and Yu, Huiqun and Fan, Guisheng and Hong, Liang},
journal={Journal of Chemical Information and Modeling},
year={2024},
publisher={ACS Publications}
}
```

许可证：Apache-2.0
任务类别：
- 文本分类
标签：
- 蛋白质（protein）
- 下游任务（downstream task）

# 基于ESMFold结构序列的GO-BP数据集

- 描述：基因本体（Gene Ontology, GO）项目的生物过程分支
- 标签数量：1943个
- 任务类型：多标签分类
- 数据列：
- aa_seq：蛋白质氨基酸序列
- foldseek_seq：foldseek 20 3di结构序列
- ss8_seq：DSSP定义的8类二级结构序列

# GitHub

简洁高效且可扩展的结构感知适配器助力蛋白质语言模型性能提升
https://github.com/tyang816/SES-Adapter

# 引用说明

若您使用本数据集，请引用我们的研究工作。

@article{tan2024ses-adapter,
title={Simple, Efficient, and Scalable Structure-Aware Adapter Boosts Protein Language Models},
author={Tan, Yang and Li, Mingchen and Zhou, Bingxin and Zhong, Bozitao and Zheng, Lirong and Tan, Pan and Zhou, Ziyi and Yu, Huiqun and Fan, Guisheng and Hong, Liang},
journal={Journal of Chemical Information and Modeling},
year={2024},
publisher={ACS Publications}
}