DEEPScreen: Virtual Screening with Deep Convolutional Neural Networks Using Compound Images

Computational Analysis of Novel Drug Opportunities

Method for drug repurposing from knowledge graphs and literature

Supplementary code for the paper: Network Medicine Framework for Identifying Drug Repurposing Opportunities for COVID-19

Source code for TKDE'22 "KG-MTL: Knowledge Graph Enhanced Multi-Task Learning for Molecular Interaction"

DeepDrugDomain: A versatile Python toolkit for streamlined preprocessing and accurate prediction of drug-target interactions and binding affinities, leveraging deep learning for advancing computational drug discovery.

A python package to explore pathways, diseases and drugs associated to a list of targets (genes, proteins, etc)

The official code implementation for DREAMwalk in Python.

Project of drug interactions https://arxiv.org/pdf/2209.09941.pdf https://arxiv.org/pdf/2302.08680.pdf, NeurIPS 2022 (AI for Science)

LigTMap currently supports prediction for 17 protein target classes that include 6000+ protein targets.

This repository provides an implementation of the DTi2Vec tool, to identify Drug-Target interaction using network embedding and ensemble learning

Generative AI-assisted Drug Repurposing Pipeline

DrugGen: Advancing Drug Discovery with Large Language Models and Reinforcement Learning Feedback

(DRExM³L) Drug REpurposing using eXplainable Machine Learning and Mechanistic Models of signal transduction

Multimodal Contrastive Representation Learning in Augmented Biomedical Knowledge Graphs

Module containing an script to perform a chemical multiverse integrating several molecular representations to generate multipe chemical spaces to provide a depper analysis of structure multiple activity relationships

ISCMF: Integrated Similarity-Constrained Matrix Factorization for Drug-Drug Interaction Prediction

An end-to-end knowledge graph based method for computational drug repurposing

Voting-averaged ensemble regression and hybrid neural networks to investigate potent leads against colorectal cancer