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A Hidden Spatial-Temporal Markov Random Field Model For Network-Based Analysis Of Time Course Gene Expression Data, Zhi Wei, Hongzhe Li
A Hidden Spatial-Temporal Markov Random Field Model For Network-Based Analysis Of Time Course Gene Expression Data, Zhi Wei, Hongzhe Li
UPenn Biostatistics Working Papers
Microarray time course (MTC) gene expression data are commonly collected to study the dynamic nature of biological processes. One important problem is to identify genes that show different expression profiles over time and pathways that are perturbed during a given biological process. While methods are available to identify the genes with differential expression levels over time, there is a lack of methods that can incorporate the pathway information in identifying the pathways being modified/activated during a biological process. In this paper, we develop a hidden spatial-temporal Markov random field (hstMRF)-based method for identifying genes and subnetworks that are related to …