A Systematic Framework for Drug Repositioning from Integrated Omics and Drug Phenotype Profiles Using Pathway-Drug Network.
Drug repositioning offers new clinical indications for old drugs. Recently, many computational approaches have been developed to repurpose marketed drugs in human diseases by mining various of biological data including disease expression profiles, pathways, drug phenotype expression profiles, and ch...
| Published in: | BioMed Research International Vol. 2016; pp. 1 - 18 |
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| Main Authors: | , |
| Format: | equations & formulas research tables/charts Journal Article |
| Published: |
Wiley-Blackwell
12/26/2016
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=120387077&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 120387077 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 12/26/2016 vid: 2016 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 120387077 120387077 120387077 10.1155/2016/7147039 120387077 ppf: 1 ppct: 17 formats: fmt: @attributes: type: P tig: atl: A Systematic Framework for Drug Repositioning from Integrated Omics and Drug Phenotype Profiles Using Pathway-Drug Network. aug: au: Jadamba, Erkhembayar Shin, Miyoung affil: Bio-Intelligence & Data Mining Laboratory, Graduate School of Electrical Engineering and Computer Science, Kyungpook National University, 1370 Sangyeok-dong, Buk-gu, Daegu 702-701, Republic of Korea sug: subj: Conceptual Framework Drug Repositioning Drugs Therapeutic Use Phenotype Drug Evaluation Genome Gene Expression Breast Neoplasms Therapy Patient Selection Female Drug Design Methods Drugs, Investigational Economics Health Care Costs Drug Approval United States Food and Drug Administration Disease Physiopathology Validation Therapy Funding Source Female ab: Drug repositioning offers new clinical indications for old drugs. Recently, many computational approaches have been developed to repurpose marketed drugs in human diseases by mining various of biological data including disease expression profiles, pathways, drug phenotype expression profiles, and chemical structure data. However, despite encouraging results, a comprehensive and efficient computational drug repositioning approach is needed that includes the high-level integration of available resources. In this study, we propose a systematic framework employing experimental genomic knowledge and pharmaceutical knowledge to reposition drugs for a specific disease. Specifically, we first obtain experimental genomic knowledge from disease gene expression profiles and pharmaceutical knowledge from drug phenotype expression profiles and construct a pathway-drug network representing a priori known associations between drugs and pathways. To discover promising candidates for drug repositioning, we initialize node labels for the pathway-drug network using identified disease pathways and known drugs associated with the phenotype of interest and perform network propagation in a semisupervised manner. To evaluate our method, we conducted some experiments to reposition 1309 drugs based on four different breast cancer datasets and verified the results of promising candidate drugs for breast cancer by a two-step validation procedure. Consequently, our experimental results showed that the proposed framework is quite useful approach to discover promising candidates for breast cancer treatment. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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