616 citations · 902 across the 19 of their papers we have counts for
19 papers
Exploring the Alignment of Generation and Understanding in Protein Structure Modeling
Junde Xu, Yuansheng Huang, Zijun Gao +5
Understanding and generation are often treated as two separate paradigms in training deep neural networks, despite the fact that both are trained with closely related objectives su…
Technical Report of HelixFold3 for Biomolecular Structure Prediction
Lihang Liu, Shanzhuo Zhang, Yang Xue +10
The AlphaFold series has transformed protein structure prediction with remarkable accuracy, often matching experimental methods. AlphaFold2, AlphaFold-Multimer, and the latest Alph…
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…
HelixFold-Multimer: Elevating Protein Complex Structure Prediction to New Heights
Xiaomin Fang, Jie Gao, Jing Hu +4
While monomer protein structure prediction tools boast impressive accuracy, the prediction of protein complex structures remains a daunting challenge in the field. This challenge i…
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…
Efficient AlphaFold2 Training using Parallel Evoformer and Branch Parallelism
Guoxia Wang, Zhihua Wu, Xiaomin Fang +4
The accuracy of AlphaFold2, a frontier end-to-end structure prediction system, is already close to that of the experimental determination techniques. Due to the complex model archi…
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…
HelixFold: An Efficient Implementation of AlphaFold2 using PaddlePaddle
Guoxia Wang, Xiaomin Fang, Zhihua Wu +6
Accurate protein structure prediction can significantly accelerate the development of life science. The accuracy of AlphaFold2, a frontier end-to-end structure prediction system, i…
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…
HelixFold-Single: MSA-free Protein Structure Prediction by Using Protein Language Model as an Alternative
Xiaomin Fang, Fan Wang, Lihang Liu +7
AI-based protein structure prediction pipelines, such as AlphaFold2, have achieved near-experimental accuracy. These advanced pipelines mainly rely on Multiple Sequence Alignments…
HelixADMET: a robust and endpoint extensible ADMET system incorporating self-supervised knowledge transfer
Shanzhuo Zhang, Zhiyuan Yan, Yueyang Huang +8
Accurate ADMET (an abbreviation for "absorption, distribution, metabolism, excretion, and toxicity") predictions can efficiently screen out undesirable drug candidates in the early…
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…
Multimodal Pre-Training Model for Sequence-based Prediction of Protein-Protein Interaction
Yang Xue, Zijing Liu, Xiaomin Fang +1
Protein-protein interactions (PPIs) are essentials for many biological processes where two or more proteins physically bind together to achieve their functions. Modeling PPIs is us…
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…
LiteGEM: Lite Geometry Enhanced Molecular Representation Learning for Quantum Property Prediction
Shanzhuo Zhang, Lihang Liu, Sheng Gao +6
In this report, we (SuperHelix team) present our solution to KDD Cup 2021-PCQM4M-LSC, a large-scale quantum chemistry dataset on predicting HOMO-LUMO gap of molecules. Our solution…
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…
MBCAL: Sample Efficient and Variance Reduced Reinforcement Learning for Recommender Systems
Fan Wang, Xiaomin Fang, Lihang Liu +2
In recommender systems such as news feed stream, it is essential to optimize the long-term utilities in the continuous user-system interaction processes. Previous works have proved…
Sequential Evaluation and Generation Framework for Combinatorial Recommender System
Fan Wang, Xiaomin Fang, Lihang Liu +5
In the combinatorial recommender systems, multiple items are fed to the user at one time in the result page, where the correlations among the items have impact on the user behavior…