616 citations · 902 across the 19 of their papers we have counts for
8 papers · 1 filter
Unifying Sequences, Structures, and Descriptions for Any-to-Any Protein Generation with the Large Multimodal Model HelixProtX
Zhiyuan Chen, Tianhao Chen, Chenggang Xie +4
Proteins are fundamental components of biological systems and can be represented through various modalities, including sequences, structures, and textual descriptions. Despite the…
Pre-Training on Large-Scale Generated Docking Conformations with HelixDock to Unlock the Potential of Protein-ligand Structure Prediction Models
Lihang Liu, Shanzhuo Zhang, Donglong He +12
Protein-ligand structure prediction is an essential task in drug discovery, predicting the binding interactions between small molecules (ligands) and target proteins (receptors). R…
DuETA: Traffic Congestion Propagation Pattern Modeling via Efficient Graph Learning for ETA Prediction at Baidu Maps
Jizhou Huang, Zhengjie Huang, Xiaomin Fang +5
Estimated time of arrival (ETA) prediction, also known as travel time estimation, is a fundamental task for a wide range of intelligent transportation applications, such as navigat…
GEM-2: Next Generation Molecular Property Prediction Network by Modeling Full-range Many-body Interactions
Lihang Liu, Donglong He, Xiaomin Fang +4
Molecular property prediction is a fundamental task in the drug and material industries. Physically, the properties of a molecule are determined by its own electronic structure, wh…
TCR: A Transformer Based Deep Network for Predicting Cancer Drugs Response
Jie Gao, Jing Hu, Wanqing Sun +5
Predicting clinical outcomes to anti-cancer drugs on a personalized basis is challenging in cancer treatment due to the heterogeneity of tumors. Traditional computational efforts h…
Docking-based Virtual Screening with Multi-Task Learning
Zijing Liu, Xianbin Ye, Xiaomin Fang +3
Machine learning shows great potential in virtual screening for drug discovery. Current efforts on accelerating docking-based virtual screening do not consider using existing data…
HelixMO: Sample-Efficient Molecular Optimization in Scene-Sensitive Latent Space
Zhiyuan Chen, Xiaomin Fang, Zixu Hua +3
Efficient exploration of the chemical space to search the candidate drugs that satisfy various constraints is a fundamental task of drug discovery. Advanced deep generative methods…
ChemRL-GEM: Geometry Enhanced Molecular Representation Learning for Property Prediction
Xiaomin Fang, Lihang Liu, Jieqiong Lei +6
Effective molecular representation learning is of great importance to facilitate molecular property prediction, which is a fundamental task for the drug and material industry. Rece…