Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/6846
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dc.contributor.authorBansal, Mukesh-
dc.contributor.authorYang, Jichen-
dc.contributor.authorKaran, Charles-
dc.contributor.authorMenden, Michael P.-
dc.contributor.authorCostello, James C.-
dc.contributor.authorTang, Hao-
dc.contributor.authorXiao, Guanghua-
dc.contributor.authorLi, Yajuan-
dc.contributor.authorAllen, Jeffrey-
dc.contributor.authorZhong, Rui-
dc.contributor.authorChen, Beibei-
dc.contributor.authorKim, Minsoo-
dc.contributor.authorWang, Tao-
dc.contributor.authorHeiser, Laura M.-
dc.contributor.authorRealubit, Ronald-
dc.contributor.authorMattioli, Michela-
dc.contributor.authorAlvarez, Mariano J.-
dc.contributor.authorShen, Yao-
dc.contributor.authorNCI-DREAM Community-
dc.contributor.authorKaraçalı, Bilge-
dc.contributor.authorGallahan, Daniel-
dc.contributor.authorSinger, Dinah-
dc.contributor.authorSaez-Rodriguez, Julio-
dc.contributor.authorXie, Yang-
dc.contributor.authorStolovitzky, Gustavo-
dc.contributor.authorCalifano, Andrea-
dc.date.accessioned2018-03-30T08:09:41Z
dc.date.available2018-03-30T08:09:41Z
dc.date.issued2014-12
dc.identifier.citationBansal, M., Yang, J., Karan, C., Menden, M. P., Costello, J. C., Tang, H., ...Califano, A. (2014). A community computational challenge to predict the activity of pairs of compounds. Nature Biotechnology, 32(12), 1213-1222. doi:10.1038/nbt.3052en_US
dc.identifier.issn1087-0156
dc.identifier.issn1546-1696-
dc.identifier.issn1087-0156-
dc.identifier.urihttp://doi.org/10.1038/nbt.3052
dc.identifier.urihttp://hdl.handle.net/11147/6846
dc.description.abstractRecent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.en_US
dc.description.sponsorshipMultiscale Analysis of Genomic and Cellular Networks (MAGNet 5U54CA121852-08); Library of Integrated Network-based Cellular Signatures Program (LINCS 1U01CA164184-02--3U01HL111566-02); National Institutes of Health (NIH 5R01CA152301); Cancer Prevention and Research Institute of Texas (CPRIT RP101251); NIH, NCI (U54 CA112970)en_US
dc.language.isoenen_US
dc.publisherNature Publishing Groupen_US
dc.relation.ispartofNature Biotechnologyen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectGene expressionen_US
dc.subjectScoring metricsen_US
dc.subjectComputational challengesen_US
dc.subjectSynergistic combinationsen_US
dc.subjectDrug combinationsen_US
dc.subjectForecastingen_US
dc.titleA community computational challenge to predict the activity of pairs of compoundsen_US
dc.typeArticleen_US
dc.authoridTR11527en_US
dc.institutionauthorKaraçalı, Bilge-
dc.departmentİzmir Institute of Technology. Electrical and Electronics Engineeringen_US
dc.identifier.volume32en_US
dc.identifier.issue12en_US
dc.identifier.startpage1213en_US
dc.identifier.endpage1222en_US
dc.identifier.wosWOS:000346156800023en_US
dc.identifier.scopus2-s2.0-84924338899en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1038/nbt.3052-
dc.identifier.pmid25419740en_US
dc.relation.doi10.1038/nbt.3052en_US
dc.coverage.doi10.1038/nbt.3052en_US
dc.identifier.wosqualityQ1-
dc.identifier.scopusqualityQ1-
dc.identifier.wosqualityttpTop10%en_US
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.grantfulltextopen-
crisitem.author.dept03.05. Department of Electrical and Electronics Engineering-
Appears in Collections:Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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