10 citations · 25 across the 10 of their papers we have counts for
10 papers
EC-Conf: An Ultra-fast Diffusion Model for Molecular Conformation Generation with Equivariant Consistency
Zhiguang Fan, Yuedong Yang, Mingyuan Xu +1
Despite recent advancement in 3D molecule conformation generation driven by diffusion models, its high computational cost in iterative diffusion/denoising process limits its applic…
Communicative Subgraph Representation Learning for Multi-Relational Inductive Drug-Gene Interaction Prediction
Jiahua Rao, Shuangjia Zheng, Sijie Mai +1
Illuminating the interconnections between drugs and genes is an important topic in drug development and precision medicine. Currently, computational predictions of drug-gene intera…
Leveraging Large-scale Computational Database and Deep Learning for Accurate Prediction of Material Properties
Pin Chen, Jianwen Chen, Hui Yan +6
Accurately predicting the physical and chemical properties of materials remains one of the most challenging tasks in material design, and one effective strategy is to construct a r…
Molecular Attributes Transfer from Non-Parallel Data
Shuangjia Zheng, Ying Song, Zhang Pan +3
Optimizing chemical molecules for desired properties lies at the core of drug development. Despite initial successes made by deep generative models and reinforcement learning metho…
Learning Attributed Graph Representations with Communicative Message Passing Transformer
Jianwen Chen, Shuangjia Zheng, Ying Song +2
Constructing appropriate representations of molecules lies at the core of numerous tasks such as material science, chemistry and drug designs. Recent researches abstract molecules…
Subgraph-aware Few-Shot Inductive Link Prediction via Meta-Learning
Shuangjia Zheng, Sijie Mai, Ya Sun +2
Link prediction for knowledge graphs aims to predict missing connections between entities. Prevailing methods are limited to a transductive setting and hard to process unseen entit…
Quantitative Evaluation of Explainable Graph Neural Networks for Molecular Property Prediction
Jiahua Rao, Shuangjia Zheng, Yuedong Yang
Advances in machine learning have led to graph neural network-based methods for drug discovery, yielding promising results in molecular design, chemical synthesis planning, and mol…
BioNavi-NP: Biosynthesis Navigator for Natural Products
Shuangjia Zheng, Tao Zeng, Chengtao Li +4
Nature, a synthetic master, creates more than 300,000 natural products (NPs) which are the major constituents of FDA-proved drugs owing to the vast chemical space of NPs. To date,…
Communicative Message Passing for Inductive Relation Reasoning
Sijie Mai, Shuangjia Zheng, Yuedong Yang +1
Relation prediction for knowledge graphs aims at predicting missing relationships between entities. Despite the importance of inductive relation prediction, most previous works are…
Predicting Retrosynthetic Reaction using Self-Corrected Transformer Neural Networks
Shuangjia Zheng, Jiahua Rao, Zhongyue Zhang +2
Synthesis planning is the process of recursively decomposing target molecules into available precursors. Computer-aided retrosynthesis can potentially assist chemists in designing…