Mingchen Li (李明辰)
I received my Ph.D. degree in Computer Science and Technology from East China University of Science and Technology,
under the supervision of Professor Huiqun Yu.
I am currently a postdoctoral researcher at Shanghai Jiao Tong University,
under the supervision of Professor Liang Hong.
My research interests lie in deep learning for protein design.
|
|
Preprints
-
Venus-MAXWELL: Efficient Learning of Protein-Mutation Stability Landscapes using Protein Language Models
Yuanxi Yu, Fan Jiang, XinZhu Ma, Liang Zhang, Bozitao Zhong, Wanli Ouyang, Guisheng Fan, Huiqun Yu, Liang Hong*, Mingchen Li*
bioRxiv, 2025
[URL] -
Discovery of Expression-Governing Residues in Proteins
Fan Jiang#, Mingchen Li#*, Banghao Wu, Liang Zhang, Bozitao Zhong, Yuanxi Yu, Liang Hong
bioRxiv, 2025
[URL] -
Harnessing A Unified Multi-modal Sequence Modeling to unveil Protein-DNA Interdependency
Mingchen Li#, Yuchen Ren#, Peng Ye#, Jiabei Cheng#, Xinzhu Ma, Yuchen Cai,
Wanli Ouyang, Bozitao Zhong, Banghao Wu, Nanqing Dong, Liang Hong, Pan Tan
bioRxiv, 2025
[URL]
Selected Publications
-
DeepSeek模型分析及其在AI辅助蛋白质工程中的应用
李明辰; 钟博子韬; 余元玺; 姜帆; 张良; 谭扬; 范贵生; 虞慧群; 洪亮
合成生物学, 2025
[URL] -
A Deep Retrieval-Enhanced Meta-Learning Framework for Enzyme Optimum pH Prediction
Liang Zhang, Kuan Luo, Ziyi Zhou, Yuanxi Yu, Fan Jiang, Banghao Wu, Mingchen Li* and Liang Hong*.
Journal of Chemical Information and Modeling, 2025
[URL] -
Entropy-driven zero-shot deep learning model selection for viral proteins
Yuanxi Yu, Fan Jiang, Bozitao Zhong, Liang Hong* and Mingchen Li*
Physical Review Research, 2025
[URL] -
A general temperature-guided language model to design proteins of enhanced stability and activity
Fan Jiang#, Mingchen Li#, Jiajun Dong#, Yuanxi Yu#, Xinyu Sun#, Banghao Wu#, Jin Huang, Liqi Kang,
Yufeng Pei, Liang Zhang, Shaojie Wang, Wenxue Xu, Jingyao Xin, Wanli Ouyang, Guisheng Fan, Lirong Zheng, Yang Tan,
Zhiqiang Hu, Yi Xiong, Yan Feng, Guangyu Yang, Qian Liu, Jie Song, Jia Liu, Liang Hong and Pan Tan
Science Advances, 2024
[URL] -
ProSST: Protein Language Modeling with Quantized Structure and Disentangled Attention
Mingchen Li#, Yang Tan#, Xinzhu Ma, Bozitao Zhong, Huiqun Yu, Ziyi Zhou, Wanli Ouyang, Bingxin Zhou, Pan Tan, Liang Hong
NeurIPS Poster, 2024
[URL] -
Learning temperature-aware representations from millions of annotated protein sequences
Mingchen Li#, Liang Zhang#, Zilan Wang, Bozitao Zhong, Pan Tan, Jiabei Cheng, Bingxin Zhou, Liang Hong, Huiqun Yu
Neurips 2024 Workshop FM4Science Oral, 2024
[URL] -
Learning to Generate Structured Code Summaries from Hybrid Code Context
Ziyi Zhou#, Mingchen Li#, Huiqun Yu, Guisheng Fan, Penghui Yang, Zijie Huang
IEEE Transactions on Software Engineering, 2024
[URL] -
Simple, efficient, and scalable structure-aware adapter boosts protein language models
Yang Tan#, Mingchen Li#, Bingxin Zhou, Bozitao Zhong, Lirong Zheng, Pan Tan, Ziyi Zhou, Huiqun Yu, Guisheng Fan, Liang Hong
Journal of Chemical Information and Modeling, 2024
[URL] -
PETA: evaluating the impact of protein transfer learning with sub-word tokenization on downstream applications
Yang Tan#, Mingchen Li#, Ziyi Zhou, Pan Tan, Huiqun Yu, Guisheng Fan, Liang Hong
Journal of Cheminformatics, 2024
[URL] -
Enhancing efficiency of protein language models with minimal wet-lab data through few-shot learning
Ziyi Zhou, Liang Zhang, Yuanxi Yu, Banghao Wu, Mingchen Li, Liang Hong, Pan Tan
Nature Communications, 2024
[URL] -
Enhancing code summarization with action word prediction
Mingchen Li, Huiqun Yu, Guisheng Fan, Ziyi Zhou, Zijie Huang
Neurocomputing, 2024
[URL] -
SESNet: sequence-structure feature-integrated deep learning method for data-efficient protein engineering
Mingchen Li#, Liqi Kang#, Yi Xiong, Yu Guang Wang, Guisheng Fan, Pan Tan, Liang Hong
Journal of Cheminformatics, 2024
[URL]