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dc.contributor.authorGedeon, Tomas
dc.contributor.authorCummins, G.
dc.contributor.authorHeys, Jeffrey J.
dc.date.accessioned2016-02-08T18:28:16Z
dc.date.available2016-02-08T18:28:16Z
dc.date.issued2012-08
dc.identifier.citationT. Gedeon, G. Cummins, and J. J. Heys, “Effect of Model Selection on Prediction of Periodic Behavior in Gene Regulatory Networks,” Bull Math Biol, vol. 74, no. 8, pp. 1706–1726, May 2012.en_US
dc.identifier.issn0092-8240
dc.identifier.urihttps://scholarworks.montana.edu/xmlui/handle/1/9543
dc.description.abstractOne of the current challenges for cell biology is understanding of the system level cellular behavior from the knowledge of a network of the individual subcellular agents. We address a question of how the model selection affects the predicted dynamic behavior of a gene network. In particular, for a fixed network structure, we compare protein-only models with models in which each transcriptional activation is represented both by mRNA and protein concentrations. We compare linear behavior near equilibria for both cyclic feedback systems and a general system. We show that, in general, explicit inclusion of the mRNA in the model weakens the stability of equilibria. We also study numerically dynamics of a particular gene network and show significant differences in global dynamics between the two types of models.en_US
dc.titleEffect of model selection on prediction of periodic behavior in gene regulatory networksen_US
dc.typeArticleen_US
mus.citation.extentfirstpage1706en_US
mus.citation.extentlastpage1726en_US
mus.citation.issue8en_US
mus.citation.journaltitleBulletin of Mathematical Biologyen_US
mus.citation.volume74en_US
mus.identifier.categoryLife Sciences & Earth Sciencesen_US
mus.identifier.categoryPhysics & Mathematicsen_US
mus.identifier.doi10.1007/s11538-012-9732-2en_US
mus.relation.collegeCollege of Letters & Scienceen_US
mus.relation.departmentMathematical Sciences.en_US
mus.relation.universityMontana State University - Bozemanen_US
mus.contributor.orcidGedeon, Tomas|0000-0001-5555-6741en_US


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