1 citations · 1 across the 5 of their papers we have counts for
5 papers
Representation-Guided Discrete Molecular Graph Retrosynthesis
Jiahai Huang, Anjie Qiao, Zhen Wang +2
Stochastic process-based molecular graph generators have become the state of the art for template-free single-step retrosynthesis. However, these models are typically trained only…
A Novel Framework for Multi-Modal Protein Representation Learning
Runjie Zheng, Zhen Wang, Anjie Qiao +3
Accurate protein function prediction requires integrating heterogeneous intrinsic signals (e.g., sequence and structure) with noisy extrinsic contexts (e.g., protein-protein intera…
A 3D pocket-aware and evolutionary conserved interaction guided diffusion model for molecular optimization
Anjie Qiao, Hao Zhang, Qianmu Yuan +7
Generating molecules that bind to specific protein targets via diffusion models has shown good promise for structure-based drug design and molecule optimization. Especially, the di…
A 3D pocket-aware and affinity-guided diffusion model for lead optimization
Anjie Qiao, Junjie Xie, Weifeng Huang +7
Molecular optimization, aimed at improving binding affinity or other molecular properties, is a crucial task in drug discovery that often relies on the expertise of medicinal chemi…
Incorporating Retrieval-based Causal Learning with Information Bottlenecks for Interpretable Graph Neural Networks
Jiahua Rao, Jiancong Xie, Hanjing Lin +3
Graph Neural Networks (GNNs) have gained considerable traction for their capability to effectively process topological data, yet their interpretability remains a critical concern.…