Graphormer is a general-purpose deep learning backbone for molecular modeling.

The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell level. CPA performs OOD predictions of unseen combinations of dr…

The Official Repo for "Quick Start Guide to Large Language Models"

A foundation model for drug synergy analysis

Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.

Implementation of Self-supervised Graph-level Representation Learning with Local and Global Structure (ICML 2021).

pytorch tutorial for beginners

TxGNN: Zero-shot prediction of therapeutic use with geometric deep learning and clinician centered design

꼼꼼한 딥러닝 논문 리뷰와 코드 실습

a molecular descriptor calculator

Community-Maintained Version of mordred

Platform for designing and evaluating Graph Neural Networks (GNN)

AGILE Platform: A Deep Learning-Powered Approach to Accelerate LNP Development for mRNA Delivery

Strategies for Pre-training Graph Neural Networks