Network-based approach to prediction and population-based validation of in silico drug repurposing

Repurposing approved drugs could accelerate treatment options for various diseases. Here, the authors use network proximity of disease gene products and drug targets in the human protein interactome to identify drug-disease associations for cardiovascular disease, and validate these using longitudin...

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Autores principales: Feixiong Cheng, Rishi J. Desai, Diane E. Handy, Ruisheng Wang, Sebastian Schneeweiss, Albert-László Barabási, Joseph Loscalzo
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2018
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Acceso en línea:https://doaj.org/article/264d3bc2952944739e5a0650a3d519eb
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spelling oai:doaj.org-article:264d3bc2952944739e5a0650a3d519eb2021-12-02T17:32:34ZNetwork-based approach to prediction and population-based validation of in silico drug repurposing10.1038/s41467-018-05116-52041-1723https://doaj.org/article/264d3bc2952944739e5a0650a3d519eb2018-07-01T00:00:00Zhttps://doi.org/10.1038/s41467-018-05116-5https://doaj.org/toc/2041-1723Repurposing approved drugs could accelerate treatment options for various diseases. Here, the authors use network proximity of disease gene products and drug targets in the human protein interactome to identify drug-disease associations for cardiovascular disease, and validate these using longitudinal healthcare data.Feixiong ChengRishi J. DesaiDiane E. HandyRuisheng WangSebastian SchneeweissAlbert-László BarabásiJoseph LoscalzoNature PortfolioarticleScienceQENNature Communications, Vol 9, Iss 1, Pp 1-12 (2018)
institution DOAJ
collection DOAJ
language EN
topic Science
Q
spellingShingle Science
Q
Feixiong Cheng
Rishi J. Desai
Diane E. Handy
Ruisheng Wang
Sebastian Schneeweiss
Albert-László Barabási
Joseph Loscalzo
Network-based approach to prediction and population-based validation of in silico drug repurposing
description Repurposing approved drugs could accelerate treatment options for various diseases. Here, the authors use network proximity of disease gene products and drug targets in the human protein interactome to identify drug-disease associations for cardiovascular disease, and validate these using longitudinal healthcare data.
format article
author Feixiong Cheng
Rishi J. Desai
Diane E. Handy
Ruisheng Wang
Sebastian Schneeweiss
Albert-László Barabási
Joseph Loscalzo
author_facet Feixiong Cheng
Rishi J. Desai
Diane E. Handy
Ruisheng Wang
Sebastian Schneeweiss
Albert-László Barabási
Joseph Loscalzo
author_sort Feixiong Cheng
title Network-based approach to prediction and population-based validation of in silico drug repurposing
title_short Network-based approach to prediction and population-based validation of in silico drug repurposing
title_full Network-based approach to prediction and population-based validation of in silico drug repurposing
title_fullStr Network-based approach to prediction and population-based validation of in silico drug repurposing
title_full_unstemmed Network-based approach to prediction and population-based validation of in silico drug repurposing
title_sort network-based approach to prediction and population-based validation of in silico drug repurposing
publisher Nature Portfolio
publishDate 2018
url https://doaj.org/article/264d3bc2952944739e5a0650a3d519eb
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AT ruishengwang networkbasedapproachtopredictionandpopulationbasedvalidationofinsilicodrugrepurposing
AT sebastianschneeweiss networkbasedapproachtopredictionandpopulationbasedvalidationofinsilicodrugrepurposing
AT albertlaszlobarabasi networkbasedapproachtopredictionandpopulationbasedvalidationofinsilicodrugrepurposing
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