DEEPScreen: Virtual Screening with Deep Convolutional Neural Networks Using Compound Images
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Updated
Jun 17, 2024 - Python
DEEPScreen: Virtual Screening with Deep Convolutional Neural Networks Using Compound Images
Supplementary code for the paper: Network Medicine Framework for Identifying Drug Repurposing Opportunities for COVID-19
Method for drug repurposing from knowledge graphs and literature
LigTMap currently supports prediction for 17 protein target classes that include 6000+ protein targets.
Computational Analysis of Novel Drug Opportunities
Source code for TKDE'22 "KG-MTL: Knowledge Graph Enhanced Multi-Task Learning for Molecular Interaction"
This repository provides an implementation of the DTi2Vec tool, to identify Drug-Target interaction using network embedding and ensemble learning
ISCMF: Integrated Similarity-Constrained Matrix Factorization for Drug-Drug Interaction Prediction
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.
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.
Project of drug interactions https://arxiv.org/pdf/2209.09941.pdf https://arxiv.org/pdf/2302.08680.pdf, NeurIPS 2022 (AI for Science)
M.Sc-final-project
Package which contains implementations of published collaborative filtering-based algorithms for drug repurposing.
The official code implementation for DREAMwalk in Python.
Drug Disease assosiation prediction
Collect and visualize network info about drugs and targets related to COVID-19
NIH AI Workshop1: Generating Molecular Features for Drug Function Classification
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