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dc.contributor.authorDettling, Marcel-
dc.contributor.authorBühlmann, Peter-
dc.date.accessioned2018-04-03T13:49:00Z-
dc.date.available2018-04-03T13:49:00Z-
dc.date.issued2004-
dc.identifier.issn0047-259Xde_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/4644-
dc.description.abstractMicroarray experiments generate large datasets with expression values for thousands of genes, but not more than a few dozens of samples. A challenging task with these data is to reveal groups of genes which act together and whose collective expression is strongly associated with an outcome variable of interest. To find these groups, we suggest the use of supervised algorithms: these are procedures which use external information about the response variable for grouping the genes. We present Pelora, an algorithm based on penalized logistic regression analysis, that combines gene selection, gene grouping and sample classification in a supervised, simultaneous way. With an empirical study on six different microarray datasets, we show that Pelora identifies gene groups whose expression centroids have very good predictive potential and yield results that can keep up with state-of-the-art classification methods based on single genes. Thus, our gene groups can be beneficial in medical diagnostics and prognostics, but they may also provide more biological insights into gene function and regulation.de_CH
dc.language.isoende_CH
dc.publisherElsevierde_CH
dc.relation.ispartofJournal of Multivariate Analysisde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectGene expressionde_CH
dc.subjectPenalized logistic regressionde_CH
dc.subjectDimension reductionde_CH
dc.subjectSample classificationde_CH
dc.subject.ddc572: Biochemiede_CH
dc.titleFinding predictive gene groups from microarray datade_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.publisher.placeAmsterdamde_CH
dc.identifier.doi10.1016/j.jmva.2004.02.012de_CH
zhaw.funding.euNode_CH
zhaw.issue1de_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end131de_CH
zhaw.pages.start106de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume90de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
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Dettling, M., & Bühlmann, P. (2004). Finding predictive gene groups from microarray data. Journal of Multivariate Analysis, 90(1), 106–131. https://doi.org/10.1016/j.jmva.2004.02.012
Dettling, M. and Bühlmann, P. (2004) ‘Finding predictive gene groups from microarray data’, Journal of Multivariate Analysis, 90(1), pp. 106–131. Available at: https://doi.org/10.1016/j.jmva.2004.02.012.
M. Dettling and P. Bühlmann, “Finding predictive gene groups from microarray data,” Journal of Multivariate Analysis, vol. 90, no. 1, pp. 106–131, 2004, doi: 10.1016/j.jmva.2004.02.012.
DETTLING, Marcel und Peter BÜHLMANN, 2004. Finding predictive gene groups from microarray data. Journal of Multivariate Analysis. 2004. Bd. 90, Nr. 1, S. 106–131. DOI 10.1016/j.jmva.2004.02.012
Dettling, Marcel, and Peter Bühlmann. 2004. “Finding Predictive Gene Groups from Microarray Data.” Journal of Multivariate Analysis 90 (1): 106–31. https://doi.org/10.1016/j.jmva.2004.02.012.
Dettling, Marcel, and Peter Bühlmann. “Finding Predictive Gene Groups from Microarray Data.” Journal of Multivariate Analysis, vol. 90, no. 1, 2004, pp. 106–31, https://doi.org/10.1016/j.jmva.2004.02.012.


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