Biologically-Interpretable Disease Classification Based on Gene Expression Data

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dc.contributor.authorGrothaus, Gregoryen
dc.contributor.committeechairMurali, T. M.en
dc.contributor.committeememberChoi, Vickyen
dc.contributor.committeememberOnufriev, Alexey V.en
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2014-03-14T20:38:47Zen
dc.date.adate2005-06-14en
dc.date.available2014-03-14T20:38:47Zen
dc.date.issued2005-05-13en
dc.date.rdate2005-06-14en
dc.date.sdate2005-05-27en
dc.description.abstractClassification of tissues and diseases based on gene expression data is a powerful application of DNA microarrays. Many popular classifiers like support vector machines, nearest-neighbour methods, and boosting have been applied successfully to this problem. However, it is difficult to determine from these classifiers which genes are responsible for the distinctions between the diseases. We propose a novel framework for classification of gene expression data based on notion of condition-specific clusters of co-expressed genes called xMotifs. Our xMotif-based classifier is biologically interpretable: we show how we can detect relationships between xMotifs and gene functional annotations. Our classifier achieves high-accuracy on leave-one-out cross-validation on both two-class and multi-class data. Our technique has the potential to be the method of choice for researchers interested in disease and tissue classification.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-05272005-145543en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-05272005-145543/en
dc.identifier.urihttp://hdl.handle.net/10919/33288en
dc.publisherVirginia Techen
dc.relation.haspartthesis.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectClassificationen
dc.subjectBiclusteringen
dc.subjectGene Expressionen
dc.subjectMicroarraysen
dc.titleBiologically-Interpretable Disease Classification Based on Gene Expression Dataen
dc.typeThesisen
thesis.degree.disciplineComputer Scienceen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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