4 citations · 10 across the 11 of their papers we have counts for
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cs.CL2023★ 2 cited
PETA: Evaluating the Impact of Protein Transfer Learning with Sub-word Tokenization on Downstream Applications
Yang Tan, Mingchen Li, Pan Tan +4
Large protein language models are adept at capturing the underlying evolutionary information in primary structures, offering significant practical value for protein engineering. Co…
cs.CL2023★ 4 cited
MedChatZH: a Better Medical Adviser Learns from Better Instructions
Yang Tan, Mingchen Li, Zijie Huang +2
Generative large language models (LLMs) have shown great success in various applications, including question-answering (QA) and dialogue systems. However, in specialized domains li…
q-bio.BM2023★ 1 cited
Pro-PRIME: A general Temperature-Guided Language model to engineer enhanced Stability and Activity in Proteins
Fan Jiang, Mingchen Li, Jiajun Dong +23
Designing protein mutants of both high stability and activity is a critical yet challenging task in protein engineering. Here, we introduce PRIME, a deep learning model, which can…