5 citations · 13 across the 15 of their papers we have counts for
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Fast and Interpretable Protein Substructure Alignment via Optimal Transport
Zhiyu Wang, Bingxin Zhou, Jing Wang +4
Proteins are essential biological macromolecules that execute life functions. Local structural motifs, such as active sites, are the most critical components for linking structure…
Sequence-Only Prediction of Binding Affinity Changes: A Robust and Interpretable Model for Antibody Engineering
Chen Liu, Mingchen Li, Yang Tan +3
A pivotal area of research in antibody engineering is to find effective modifications that enhance antibody-antigen binding affinity. Traditional wet-lab experiments assess mutants…
VenusMutHub: A systematic evaluation of protein mutation effect predictors on small-scale experimental data
Liang Zhang, Hua Pang, Chenghao Zhang +11
In protein engineering, while computational models are increasingly used to predict mutation effects, their evaluations primarily rely on high-throughput deep mutational scanning (…
Protein Representation Learning with Sequence Information Embedding: Does it Always Lead to a Better Performance?
Yang Tan, Lirong Zheng, Bozitao Zhong +2
Deep learning has become a crucial tool in studying proteins. While the significance of modeling protein structure has been discussed extensively in the literature, amino acid type…
ProtSolM: Protein Solubility Prediction with Multi-modal Features
Yang Tan, Jia Zheng, Liang Hong +1
Understanding protein solubility is essential for their functional applications. Computational methods for predicting protein solubility are crucial for reducing experimental costs…