Zhuzhu Wei's Projects
Calculate the RMSD between two antibody structure (including nanobody and antibody).
PyTorch code for KDD 2023 paper "Pre-training Antibody Language Models for Antigen-Specific Computational Antibody Design"
AI-powered ab initio biomolecular dynamics simulation
Artificial Intelligence for Science (AIRS)
A curated list of Hypergraph Learning, Hypergraph Theory, Hypergraph Dataset and Hypergraph Tool.
[IJCAI 2023 survey track]A curated list of resources for chemical pre-trained models
Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).
A PyTorch hub of denoising diffusion probabilistic models designed to generate novel biological data
Protein Function Prediction competition on Kaggle
Use ChatGPT to summarize the arXiv papers. 全流程加速科研,利用chatgpt进行论文全文总结+专业翻译+润色+审稿+审稿回复
Message Passing Neural Networks for Molecule Property Prediction
A generative model for programmable protein design
Complete solutions for Stanford CS224n, winter, 2019
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
The official implementation for ICLR23 spotlight paper "DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion"
A library for graph deep learning research
drugbank相关数据的处理,包括获取药物sdf结构文件,drug相关信息,drug作用相关蛋白信息,drugbank中drug id与其他数据库的映射,protein蛋白相关信息到其他数据库的映射
Predicting Drug Protein Interaction using Quasi-Visual Question Answering System
This repo contains the codes for our paper "End-to-End Full-Atom Antibody Design"
Graph Neural Networks for Explainable Ejection Fraction Estimation
[ICLR'23 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
Implementation of the Equiformer, SE3/E3 equivariant attention network that reaches new SOTA, and adopted for use by EquiFold for protein folding
[arXiv'23] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
FABind: Fast and Accurate Protein-Ligand Binding (NIPS 2023)
Foldseek enables fast and sensitive comparisons of large structure sets.
Must-read papers on graph neural networks (GNN)
Graph-based machine learning for chemical property prediction