Bayesian Functional Data Clustering for Temporal Microarray Data

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Bayesian Functional Data Clustering for Temporal Microarray Data

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dc.contributor.author Ma, Ping
dc.contributor.author Zhong, Wenxuan
dc.contributor.author Feng, Yang
dc.contributor.author Liu, Jun
dc.date.accessioned 2010-10-05T15:43:13Z
dc.date.issued 2008
dc.identifier.citation Ma, Ping, Wenxuan Zhong, Yang Feng, and Jun S. Liu. 2008. Bayesian Functional Data Clustering for Temporal Microarray Data. International Journal of Plant Genomics 2008: 231897. en_US
dc.identifier.issn 1687-5370 en_US
dc.identifier.uri http://nrs.harvard.edu/urn-3:HUL.InstRepos:4457706
dc.description.abstract We propose a Bayesian procedure to cluster temporal gene expression microarray profiles, based on a mixed-effect smoothing-spline model, and design a Gibbs sampler to sample from the desired posterior distribution. Our method can determine the cluster number automatically based on the Bayesian information criterion, and handle missing data easily. When applied to a microarray dataset on the budding yeast, our clustering algorithm provides biologically meaningful gene clusters according to a functional enrichment analysis. en_US
dc.description.sponsorship Statistics en_US
dc.language.iso en_US en_US
dc.publisher Hindawi Publishing Corporation en_US
dc.relation.isversionof doi:10.1155/2008/231897 en_US
dc.relation.hasversion http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2358942/pdf/ en_US
dash.license LAA
dc.title Bayesian Functional Data Clustering for Temporal Microarray Data en_US
dc.type Journal Article en_US
dc.description.version Version of Record en_US
dc.relation.journal International Journal of Plant Genomics en_US
dash.depositing.author Liu, Jun
dc.date.available 2010-10-05T15:43:13Z

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  • FAS Scholarly Articles [7078]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University

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