A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
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Updated
Jun 10, 2024 - Jupyter Notebook
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
A knowledge graph and a set of tools for drug repurposing
Hetionet: an integrative network of disease
Jupyter Dock is a set of Jupyter Notebooks for performing molecular docking protocols interactively, as well as visualizing, converting file formats and analyzing the results.
DEEPScreen: Virtual Screening with Deep Convolutional Neural Networks Using Compound Images
A collection of resources for Deep Learning in Python for Life Sciences (with focus on biotech and pharma).
Readings for "A Unified View of Relational Deep Learning for Drug Pair Scoring." (IJCAI 2022)
Awesome list of computational biology.
Computational Analysis of Novel Drug Opportunities
Method for drug repurposing from knowledge graphs and literature
Scripts and resources to create Hetionet v1.0, a heterogeneous network for drug repurposing
Cataloging pharmacotherapies in clinical trial from ClinicalTrials.gov
Source code for TKDE'22 "KG-MTL: Knowledge Graph Enhanced Multi-Task Learning for Molecular Interaction"
Processed Cell Painting Data for the LINCS Drug Repurposing Project
Supplementary code for the paper: Network Medicine Framework for Identifying Drug Repurposing Opportunities for COVID-19
Single-Cell (Perturbation) Model Library
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.
single-cell and bulk RNA-seq analyses from counts → pathways → drug candidates.
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