Process Pathway Inference via Time Series Analysis

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dc.creatorWiggins, Chris
dc.creatorNemenman, Ilya
dc.date2002-06-12
dc.date.accessioned2026-07-07T05:47:41Z
dc.date.available2026-07-07T05:47:41Z
dc.descriptionMotivated by recent experimental developments in functional genomics, we construct and test a numerical technique for inferring it 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 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.
dc.identifierhttps://arxiv.org/abs/physics/0206031
dc.identifierhttp://arxiv.org/abs/physics/0206031
dc.identifierExperim. Mech., 43(3), 2003
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/84745
dc.subjectBiological Physics
dc.subjectData Analysis, Statistics and Probability
dc.subjectGenomics
dc.subjectQuantitative Methods
dc.titleProcess Pathway Inference via Time Series Analysis
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