DEEPScreen: Virtual Screening with Deep Convolutional Neural Networks Using Compound Images
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Updated
Apr 28, 2024 - Python
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
Source code for TKDE'22 "KG-MTL: Knowledge Graph Enhanced Multi-Task Learning for Molecular Interaction"
Supplementary code for the paper: Network Medicine Framework for Identifying Drug Repurposing Opportunities for COVID-19
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)
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.
This repository provides an implementation of the DTi2Vec tool, to identify Drug-Target interaction using network embedding and ensemble learning
LigTMap currently supports prediction for 17 protein target classes that include 6000+ protein targets.
ISCMF: Integrated Similarity-Constrained Matrix Factorization for Drug-Drug Interaction Prediction
M.Sc-final-project
Voting-averaged ensemble regression and hybrid neural networks to investigate potent leads against colorectal cancer
An end-to-end knowledge graph based method for computational drug repurposing
Metabolic Drug Repurposing Pipeline
(DRExM³L) Drug REpurposing using eXplainable Machine Learning and Mechanistic Models of signal transduction
Official code repository for " Deep Graph Networks for Drug Repurposing with Multi-Protein Targets".
Code and Datasets for the paper "A deep learning framework for high-throughput mechanism-driven phenotype compound screening and its application to COVID-19 drug repurposing", published on Nature Machine Intelligence in 2021.
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