A genome-wide positioning systems network algorithm for in silico drug repurposing

Identification of disease modules in the human interactome can guide more efficacious therapeutic selections. Here, the authors introduce a network-based methodology to identify individualized disease modules by mapping patients’ DNA and RNA sequencing profiles to the interactome, enabling predictio...

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Main Authors:	Feixiong Cheng, Weiqiang Lu, Chuang Liu, Jiansong Fang, Yuan Hou, Diane E. Handy, Ruisheng Wang, Yuzheng Zhao, Yi Yang, Jin Huang, David E. Hill, Marc Vidal, Charis Eng, Joseph Loscalzo
Format:	Article
Language:	English
Published:	Nature Publishing Group 2019-08-01
Series:	Nature Communications
Online Access:	https://doi.org/10.1038/s41467-019-10744-6

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spelling	doaj-2278ae537ce04f0091ede24882da7dbe2021-05-11T11:55:53ZengNature Publishing GroupNature Communications2041-17232019-08-0110111410.1038/s41467-019-10744-6A genome-wide positioning systems network algorithm for in silico drug repurposingFeixiong Cheng0Weiqiang Lu1Chuang Liu2Jiansong Fang3Yuan Hou4Diane E. Handy5Ruisheng Wang6Yuzheng Zhao7Yi Yang8Jin Huang9David E. Hill10Marc Vidal11Charis Eng12Joseph Loscalzo13Genomic Medicine Institute, Lerner Research Institute, Cleveland ClinicShanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal UniversityAlibaba Research Center for Complexity Sciences, Hangzhou Normal UniversityGenomic Medicine Institute, Lerner Research Institute, Cleveland ClinicGenomic Medicine Institute, Lerner Research Institute, Cleveland ClinicDepartment of Medicine, Brigham and Women’s Hospital, Harvard Medical SchoolDepartment of Medicine, Brigham and Women’s Hospital, Harvard Medical SchoolShanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and TechnologyShanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and TechnologyShanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and TechnologyCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer InstituteCenter for Cancer Systems Biology (CCSB), Dana-Farber Cancer InstituteGenomic Medicine Institute, Lerner Research Institute, Cleveland ClinicDepartment of Medicine, Brigham and Women’s Hospital, Harvard Medical SchoolIdentification of disease modules in the human interactome can guide more efficacious therapeutic selections. Here, the authors introduce a network-based methodology to identify individualized disease modules by mapping patients’ DNA and RNA sequencing profiles to the interactome, enabling prediction of cancer type-specific drug responses.https://doi.org/10.1038/s41467-019-10744-6
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Feixiong Cheng Weiqiang Lu Chuang Liu Jiansong Fang Yuan Hou Diane E. Handy Ruisheng Wang Yuzheng Zhao Yi Yang Jin Huang David E. Hill Marc Vidal Charis Eng Joseph Loscalzo
spellingShingle	Feixiong Cheng Weiqiang Lu Chuang Liu Jiansong Fang Yuan Hou Diane E. Handy Ruisheng Wang Yuzheng Zhao Yi Yang Jin Huang David E. Hill Marc Vidal Charis Eng Joseph Loscalzo A genome-wide positioning systems network algorithm for in silico drug repurposing Nature Communications
author_facet	Feixiong Cheng Weiqiang Lu Chuang Liu Jiansong Fang Yuan Hou Diane E. Handy Ruisheng Wang Yuzheng Zhao Yi Yang Jin Huang David E. Hill Marc Vidal Charis Eng Joseph Loscalzo
author_sort	Feixiong Cheng
title	A genome-wide positioning systems network algorithm for in silico drug repurposing
title_short	A genome-wide positioning systems network algorithm for in silico drug repurposing
title_full	A genome-wide positioning systems network algorithm for in silico drug repurposing
title_fullStr	A genome-wide positioning systems network algorithm for in silico drug repurposing
title_full_unstemmed	A genome-wide positioning systems network algorithm for in silico drug repurposing
title_sort	genome-wide positioning systems network algorithm for in silico drug repurposing
publisher	Nature Publishing Group
series	Nature Communications
issn	2041-1723
publishDate	2019-08-01
description	Identification of disease modules in the human interactome can guide more efficacious therapeutic selections. Here, the authors introduce a network-based methodology to identify individualized disease modules by mapping patients’ DNA and RNA sequencing profiles to the interactome, enabling prediction of cancer type-specific drug responses.
url	https://doi.org/10.1038/s41467-019-10744-6
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A genome-wide positioning systems network algorithm for in silico drug repurposing

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