Author

Shen Li

ORCID 0000-0002-0087-9794Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Shen Li1 paper · Imperial College London

Biology Disciplines

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Bioinformatics· 1 Synthetic Biology· 1

Signature Assays, Organisms & Methods

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Approach:large language model· 2 Assay:protein sequence· 2 Research Focus:sequence-to-function modeling· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Organism:multiple species· 1 Research Focus:protein design· 1 Assay:protein structure· 1

Frequent Co-Authors

Le SongiD· 2 shared Xingyi ChengiD· 2 shared Aohan ZengiD· 1 shared Bo CheniD· 1 shared Boyan WangiD· 1 shared Chi-Ming LiuiD· 1 shared Danielle Ann GrotjahniD· 1 shared Digvijay SinghiD· 1 shared

Activity by Year

2023-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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2 shared papersBioinformatics

Le SongORCID

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2 papers

Recent·Most cited

Multi-Modal Large Language Model Enables Protein Function Prediction

Mingjia Huo, Han Wen Guo, Xingyi Cheng, Digvijay Singh, Hamidreza Rahmani, Shen Li, Philipp Gerlof, Trey E. Ideker, Danielle Ann Grotjahn, Elizabeth Villa, Le Song, Pengtao Xie

ProteinChat is a multi-modal large language model that predicts protein functions from amino acid sequences, outperforming general-purpose LLMs and task-specific models.

bioRxiv · Aug 19, 2024 · PreprintBioinformatics

xTrimoPGLM: Unified 100B-Scale Pre-trained Transformer for Deciphering the Language of Protein

Bo Chen, Xingyi Cheng, Pan Li, Yangli‐ao Geng, Jing Gong, Shen Li, Zhilei Bei, Xu Tan, Boyan Wang, Xin Ying Zeng, Chi-Ming Liu, Aohan Zeng, Yuxiao Dong, Jie Tang, Le Song

A 100-billion-parameter protein language model trained with masked and autoregressive objectives together, topping prior results on 15 of 18 benchmarks and powering a fast structure predictor.

bioRxiv · Jul 5, 2023 · PreprintSynthetic Biology✦ In-depth digest