Update README.md (#1)

- Update README.md (828cf2cb92e52eebd3ae1e92ada083f5a4ac2910)


Co-authored-by: moyu <[email protected]>

README.md

@@ -1,34 +1,45 @@
----
-license: apache-2.0
-task_categories:
-- text-classification
-tags:
-- protein
-- downstream task
----
-
-# EC Dataset
-
-- Description: The Enzyme Commission number (EC number) is a numerical classification scheme for enzymes, based on the chemical reactions they catalyze.
-- Number of labels: 585
-- Problem Type: multi_label_classification
-- Columns:
-  - aa_seq: protein amino acid 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}
-}
+---
+license: apache-2.0
+task_categories:
+- text-classification
+tags:
+- protein
+- downstream task
+---
+
+# EC Dataset
+
+- Description: The Enzyme Commission number (EC number) is a numerical classification scheme for enzymes, based on the chemical reactions they catalyze.
+- Number of labels: 585
+- Problem Type: multi_label_classification
+- Columns:
+  - aa_seq: protein amino acid sequence
+
+# Github
+
+Simple, Efficient and Scalable Structure-aware Adapter Boosts Protein Language Models
+
+https://github.com/tyang816/SES-Adapter
+
+VenusFactory: A Unified Platform for Protein Engineering Data Retrieval and Language Model Fine-Tuning
+
+https://github.com/ai4protein/VenusFactory
+
+# 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}
+}
+
+@article{tan2025venusfactory,
+  title={VenusFactory: A Unified Platform for Protein Engineering Data Retrieval and Language Model Fine-Tuning},
+  author={Tan, Yang and Liu, Chen and Gao, Jingyuan and Wu, Banghao and Li, Mingchen and Wang, Ruilin and Zhang, Lingrong and Yu, Huiqun and Fan, Guisheng and Hong, Liang and Zhou, Bingxin},
+  journal={arXiv preprint arXiv:2503.15438},
+  year={2025}
+}
 ```