A family tree of Markov models in systems biology

dc.creatorUllah, Mukhtar
dc.creatorWolkenhauer, Olaf
dc.date2006-10-01
dc.date2007-07-11
dc.date.accessioned2026-07-07T08:23:15Z
dc.date.available2026-07-07T08:23:15Z
dc.descriptionMotivated by applications in systems biology, we seek a probabilistic framework based on Markov processes to represent intracellular processes. We review the formal relationships between different stochastic models referred to in the systems biology literature. As part of this review, we present a novel derivation of the differential Chapman-Kolmogorov equation for a general multidimensional Markov process made up of both continuous and jump processes. We start with the definition of a time-derivative for a probability density but place no restrictions on the probability distribution, in particular, we do not assume it to be confined to a region that has a surface (on which the probability is zero). In our derivation, the master equation gives the jump part of the Markov process while the Fokker-Planck equation gives the continuous part. We thereby sketch a {}``family tree'' for stochastic models in systems biology, providing explicit derivations of their formal relationship and clarifying assumptions involved.
dc.description18 pages, 2 figures
dc.identifierhttps://arxiv.org/abs/q-bio/0610003
dc.identifierhttp://arxiv.org/abs/q-bio/0610003
dc.identifierIET Syst Biol. 1 (2007) 247-254
dc.identifierdoi:10.1049/iet-syb:20070017
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/135928
dc.subjectQuantitative Methods
dc.titleA family tree of Markov models in systems biology
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