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Gene expression associations with the growth inhibitory effects of small molecules on live cells: Specificity of effects and uniformity of mechanisms

dc.contributor.authorShedden, Kerby A.en_US
dc.contributor.authorYang, Yangen_US
dc.contributor.authorRosania, Gustavo R.en_US
dc.date.accessioned2009-09-02T14:37:47Z
dc.date.available2010-10-05T18:27:29Zen_US
dc.date.issued2009-09en_US
dc.identifier.citationShedden, Kerby; Yang, Yang; Rosania, Gus (2009). "Gene expression associations with the growth inhibitory effects of small molecules on live cells: Specificity of effects and uniformity of mechanisms." Statistical Analysis and Data Mining 2(3): 175-185. <http://hdl.handle.net/2027.42/63592>en_US
dc.identifier.issn1932-1864en_US
dc.identifier.issn1932-1872en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/63592
dc.description.abstractThe NCI60 human tumor cell line screen is a public resource for studying selective and nonselective growth inhibition of small molecules against cancer cells. By coupling growth inhibition screening data with biological characterizations of the different cell lines, it becomes possible to infer mechanisms of action underlying some of the observable patterns of selective activity. Using these data, mechanistic relationships have been identified including specific associations between single genes and small families of closely related compounds, and less specific relationships between biological processes involving several cooperating genes and broader families of compounds. Here, we aim to characterize the degree to which such specific and general relationships are present in these data. A related question is whether genes tend to act with a uniform mechanism for all associated compounds, or whether multiple mechanisms are commonly involved. We address these two issues in a statistical framework placing special emphasis on the effects of measurement error in the gene expression and chemical screening data. We find that as measurement accuracy increases, the pattern of apparent associations shifts from one dominated by isolated gene/compound pairs, to one in which families consisting of an average of 25 compounds are associated to the same gene. At the same time, the number of genes that appear to play a role in influencing compound activities decreases. For less than half of the genes, the presence of both positive and negative correlations indicates pleiotropic associations with molecules via different mechanisms of action. Copyright © 2009 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 2: 175–185, 2009en_US
dc.format.extent175221 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.publisherWiley Subscription Services, Inc., A Wiley Companyen_US
dc.subject.otherStatisticsen_US
dc.subject.otherMathematics and Statisticsen_US
dc.titleGene expression associations with the growth inhibitory effects of small molecules on live cells: Specificity of effects and uniformity of mechanismsen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Statistics, University of Michigan, Ann Arbor, MI, USA ; Department of Statistics, University of Michigan, Ann Arbor, MI, USAen_US
dc.contributor.affiliationumDepartment of Statistics, University of Michigan, Ann Arbor, MI, USAen_US
dc.contributor.affiliationumDepartment of Pharmaceutical Sciences, College of Pharmacy, University of Michigan, Ann Arbor, MI, USAen_US
dc.identifier.pmid20657799en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/63592/1/10049_ftp.pdf
dc.identifier.doi10.1002/sam.10049en_US
dc.identifier.sourceStatistical Analysis and Data Miningen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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