58 citations · 79 across the 7 of their papers we have counts for
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q-bio.QM2023
Machine Learning Force Fields with Data Cost Aware Training
Alexander Bukharin, Tianyi Liu, Shengjie Wang +4
Machine learning force fields (MLFF) have been proposed to accelerate molecular dynamics (MD) simulation, which finds widespread applications in chemistry and biomedical research.…
q-bio.QM2022★ 58 cited
A fully differentiable ligand pose optimization framework guided by deep learning and traditional scoring functions
Zechen Wang, Liangzhen Zheng, Sheng Wang +6
The machine learning (ML) and deep learning (DL) techniques are widely recognized to be powerful tools for virtual drug screening. The recently reported ML- or DL-based scoring fun…
q-bio.QM2022
ProTranslator: zero-shot protein function prediction using textual description
Hanwen Xu, Sheng Wang
Accurately finding proteins and genes that have a certain function is the prerequisite for a broad range of biomedical applications. Despite the encouraging progress of existing co…