AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.

A simple MaveDB API wrapper

MaveDB API

AI-powered ab initio biomolecular dynamics simulation

A collection of resources useful for leveraging big data and AI for drug discovery. It mainly serves as an orientation for new lab folks. It may be biased towards my lab interest.

Practical AI/ML for Computational Biology and Chemistry Workshop

A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery (EMNLP'24)

Ranking, acceptance rate, deadline, and publication tips

A Protein Large Language Model for Multi-Task Protein Language Processing

A list of computational social science (CSS) program, people and groups

Open source implementation of AlphaFold3

Implementation of Alphafold 3 from Google Deepmind in Pytorch

Uncertainty-aware Self-training

Self-Training/Self-Learning

A curated list of resources for Partial-Multi-Label-Learning

Source code for AAAI 2024 paper: Compositional Generalization for Multi-Label Text Classification: A Data-Augmentation Approach

Writing AI Conference Papers: A Handbook for Beginners

Latex code for making neural networks diagrams

Publication-ready NN-architecture schematics.

[IJCAI 2023 survey track]A curated list of resources for chemical pre-trained models

bert-loves-chemistry: a repository of HuggingFace models applied on chemical SMILES data for drug design, chemical modelling, etc.

Code for paper "Mapping the combinatorial coding between olfactory receptors and perception with deep learning"

Source code accompanying the 'Transfer learning with graph neural networks for improved molecular property prediction in the multi-fidelity setting' paper

Message Passing Neural Networks for Molecule Property Prediction

ChemBFN: Bayesian Flow Network Framework for Chemistry Tasks.