Cluster-based network model for time-course gene expression data
Data(s) |
2007
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Resumo |
We propose a model-based approach to unify clustering and network modeling using time-course gene expression data. Specifically, our approach uses a mixture model to cluster genes. Genes within the same cluster share a similar expression profile. The network is built over cluster-specific expression profiles using state-space models. We discuss the application of our model to simulated data as well as to time-course gene expression data arising from animal models on prostate cancer progression. The latter application shows that with a combined statistical/bioinformatics analyses, we are able to extract gene-to-gene relationships supported by the literature as well as new plausible relationships. |
Identificador | |
Publicador |
Oxford University Press |
Relação |
DOI:10.1093/biostatistics/kxl026 Inoue, Lurdes, Neira, Mauricio, Nelson, Colleen, Gleave, Martin, & Etzioni, Ruth (2007) Cluster-based network model for time-course gene expression data. Biostatistics, 8(3), pp. 507-525. |
Fonte |
Faculty of Health; Institute of Health and Biomedical Innovation |
Palavras-Chave | #010400 STATISTICS #060400 GENETICS #Bayesian network; Bioinformatics; Dynamic linear model; Mixture model; Model-based clustering; Prostate cancer; Time-course gene expression |
Tipo |
Journal Article |