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Process Pathway Inference via Time Series Analysis

By C. H. Wiggins and I. Nemenman


ABSTRACT—Motivated by recent experimental developments in functional genomics, we construct and test a numerical technique for inferring process pathways, in which one process calls another process, from time series data. We validate using a case in which data are readily available and we formulate an extension, appropriate for genetic regulatory networks, which exploits Bayesian inference and in which the present-day undersampling is compensated for by prior understanding of genetic regulation. KEY WORDS—Genomics, pathways, gene expression regulation, Bayesian statistics, auto-regressive model

Year: 2003
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