Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/13629
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dc.contributor.authorVAN SANDEN, Suzy-
dc.contributor.authorSHKEDY, Ziv-
dc.contributor.authorBURZYKOWSKI, Tomasz-
dc.contributor.authorGohlmann, Hinrich W. H.-
dc.contributor.authorTALLOEN, Willem-
dc.contributor.authorBIJNENS, Luc-
dc.date.accessioned2012-05-02T09:33:18Z-
dc.date.available2012-05-02T09:33:18Z-
dc.date.issued2012-
dc.identifier.citationJOURNAL OF BIOPHARMACEUTICAL STATISTICS, 22 (1), p. 72-92-
dc.identifier.issn1054-3406-
dc.identifier.urihttp://hdl.handle.net/1942/13629-
dc.description.abstractIn this article, we discuss methods to select three different types of genes (treatment related, response related, or both) and investigate whether they can serve as biomarkers for a binary outcome variable. We consider an extension of the joint model introduced by Lin et al. (2010) and Tilahun et al. (2010) for a continuous response. As the model has certain drawbacks in a binary setting, we also present a way to use classical selection methods to identify subgroups of genes, which are treatment and/or response related. We evaluate their potential to serve as biomarkers by applying DLDA to predict the response level.-
dc.description.sponsorshipWe gratefully acknowledge support of the IAP research network P6/03 of the Belgian Government (Belgian Science Policy).-
dc.language.isoen-
dc.publisherTAYLOR & FRANCIS INC-
dc.subject.otherBiomarkers; BW ratio; Categorical data; Joint modeling; Microarrays-
dc.subject.otherPharmacology & Pharmacy; Statistics & Probability; Biomarkers; BW ratio; Categorical data; Joint Modeling; Microarrays-
dc.titleGenomic biomarkers for a binary clinical outcome in early drug development microarray experiments-
dc.typeJournal Contribution-
dc.identifier.epage92-
dc.identifier.issue1-
dc.identifier.spage72-
dc.identifier.volume22-
local.format.pages21-
local.bibliographicCitation.jcatA1-
dc.description.notes[Van Sanden, Suzy; Shkedy, Ziv; Burzykowski, Tomasz] Univ Hasselt, Interuniv Inst Biostat & Stat Bioinformat, B-3590 Diepenbeek, Belgium. [Shkedy, Ziv; Burzykowski, Tomasz] Katholieke Univ Leuven, Louvain, Belgium. [Van Sanden, Suzy; Gohlmann, Hinrich W. H.; Talloen, Willem; Bijnens, Luc] Johnson & Johnson, PRD, Beerse, Belgium. svsande1@its.jnj.com-
local.publisher.placePHILADELPHIA-
local.type.refereedRefereed-
local.type.specifiedArticle-
dc.bibliographicCitation.oldjcatA1-
dc.identifier.doi10.1080/10543406.2010.504906-
dc.identifier.isi000302064800006-
item.fulltextWith Fulltext-
item.contributorVAN SANDEN, Suzy-
item.contributorSHKEDY, Ziv-
item.contributorBURZYKOWSKI, Tomasz-
item.contributorGohlmann, Hinrich W. H.-
item.contributorTALLOEN, Willem-
item.contributorBIJNENS, Luc-
item.fullcitationVAN SANDEN, Suzy; SHKEDY, Ziv; BURZYKOWSKI, Tomasz; Gohlmann, Hinrich W. H.; TALLOEN, Willem & BIJNENS, Luc (2012) Genomic biomarkers for a binary clinical outcome in early drug development microarray experiments. In: JOURNAL OF BIOPHARMACEUTICAL STATISTICS, 22 (1), p. 72-92.-
item.accessRightsOpen Access-
item.validationecoom 2013-
crisitem.journal.issn1054-3406-
crisitem.journal.eissn1520-5711-
Appears in Collections:Research publications
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