Clustering of time course gene-expression data via mixture regression models
Seminar Room 1, Newton Institute
In this paper, we consider the use of mixtures of linear mixed models to cluster data which may be correlated and replicated and which may have covariates. This approach can thus be used to cluster time series data. For each cluster, a regression model is adopted to incorporate the covariates, and the correlation and replication structure in the data are specified by the inclusion of random effects terms. The procedure is illustrated in its application to the clustering of time-course gene expression data.
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