Team J-SCAMP's project for BioDataHack. Repurposing drugs through unsupervised machine learning.
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Updated
Jul 7, 2018 - Python
Team J-SCAMP's project for BioDataHack. Repurposing drugs through unsupervised machine learning.
M.Sc-final-project
NIH AI Workshop1: Generating Molecular Features for Drug Function Classification
Drug Disease assosiation prediction
Code and Datasets for the paper "A deep learning framework for drug repurposing via emulating clinical trials on real-world patient data", published on Nature Machine Intelligence in 2021.
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.
Method for drug repurposing from knowledge graphs and literature
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
Supplementary code for the paper: Network Medicine Framework for Identifying Drug Repurposing Opportunities for COVID-19
Code for the paper "Clinical connectivity map for drug repurposing: using laboratory results to bridge drugs and diseases". Accepted by BMC Medical Informatics and Decision Making, 2021
This repository provides an implementation of the DTi2Vec tool, to identify Drug-Target interaction using network embedding and ensemble learning
Code and Datasets for the paper "Chemical-induced gene expression ranking and its application to pancreatic cancer drug repurposing", published on Patterns in 2022.
Official code repository for "Controlling astrocyte-mediated synaptic pruning signals for schizophrenia drug repurposing with Deep Graph Networks".
Querying a Language model in a residual path for drug-target interaction task
Voting-averaged ensemble regression and hybrid neural networks to investigate potent leads against colorectal cancer
Drug Repurposing framed as link prediction problem, solved with Knowledge Graph Embedding (KGE). University project.
Source code for TKDE'22 "KG-MTL: Knowledge Graph Enhanced Multi-Task Learning for Molecular Interaction"
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