63 citations · 117 across the 6 of their papers we have counts for
6 papers
From Static to Dynamic Structures: Improving Binding Affinity Prediction with Graph-Based Deep Learning
Yaosen Min, Ye Wei, Peizhuo Wang +10
Accurate prediction of protein-ligand binding affinities is an essential challenge in structure-based drug design. Despite recent advances in data-driven methods for affinity predi…
KPGT: Knowledge-Guided Pre-training of Graph Transformer for Molecular Property Prediction
Han Li, Dan Zhao, Jianyang Zeng
Designing accurate deep learning models for molecular property prediction plays an increasingly essential role in drug and material discovery. Recently, due to the scarcity of labe…
BERE: An accurate distantly supervised biomedical entity relation extraction network
Lixiang Hong, JinJian Lin, Jiang Tao +1
Automated entity relation extraction (RE) from literature provides an important source for constructing biomedical database, which is more efficient and extensible than manual cura…
DeepPicker: a Deep Learning Approach for Fully Automated Particle Picking in Cryo-EM
Feng Wang, Huichao Gong, Gaochao liu +5
Particle picking is a time-consuming step in single-particle analysis and often requires significant interventions from users, which has become a bottleneck for future automated el…
Low-density locality-sensitive hashing boosts metagenomic binning
Yunan Luo, Jianyang Zeng, Bonnie Berger +1
Metagenomic binning is an essential task in analyzing metagenomic sequence datasets. To analyze structure or function of microbial communities from environmental samples, metagenom…
Computational Protein Design Using AND/OR Branch-and-Bound Search
Yichao Zhou, Yuexin Wu, Jianyang Zeng
The computation of the global minimum energy conformation (GMEC) is an important and challenging topic in structure-based computational protein design. In this paper, we propose a…