Systematic integration of biomedical knowledge prioritizes drugs for repurposing

This manuscript was published in eLife on September 22, 2017. The DOI-citable version is available at https://doi.org/10.7554/eLife.26726.

Systematic integration of biomedical knowledge prioritizes drugs for repurposing This manuscript was published in eLife on September 22, 2017. The DOI-citable version is available at https://doi.org/10.7554/eLife.26726 . This manuscript ( permalink ) was automatically generated from dhimmel/rephetio-manuscript@aad8576 on January 31, 2023. Published: September 22, 2017 Authors Daniel S. Himmelstein 0000-0002-3012-7446 · dhimmel · dhimmel Program in Biological & Medical Informatics, University of California, San Francisco; Department of Systems Pharmacology & Translational Therapeutics, Universi

related reading

• Our hetnet edge prediction methodology: the modeling framework for Project Rephetio | Thinklabthink-lab.github.io
• Using Interpretability to Identify a Novel Class of Alzheimer's Biomarkersgoodfire.ai
• The Building Blocks of Interpretabilitydistill.pub
• The coming age of data-driven medicine: translational bioinformatics' next frontierpmc.ncbi.nlm.nih.gov
• TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discoveryarxiv.org
• An experimentally validated approach to automated biological evidence generation in drug discovery using knowledge graphs | Nature Communicationsnature.com
• Overview | Human Brain Pharmacomepharmacome.github.io
• the drug landscapegenome-browser-eight.vercel.app
• One network to rule them all | Thinklabthink-lab.github.io
• Accelerating science with human-aware artificial intelligencenature.com
• Linking chemical and disease entities to ontologies by integrating PageRank with extracted relations from literature | Journal of Cheminformatics | Springer Nature Linkjcheminf.biomedcentral.com
• PREDICTING SINGLE-CELL PERTURBATION RESPONSES FOR UNSEEN DRUGSarxiv.org