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dc.contributor.authorLakatos, E
dc.contributor.authorStumpf, MPH
dc.date.accessioned2020-12-10T00:17:57Z
dc.date.available2020-12-10T00:17:57Z
dc.date.issued2017-08-01
dc.identifierpii: rsos160790
dc.identifier.citationLakatos, E. & Stumpf, M. P. H. (2017). Control mechanisms for stochastic biochemical systems via computation of reachable sets. ROYAL SOCIETY OPEN SCIENCE, 4 (8), https://doi.org/10.1098/rsos.160790.
dc.identifier.issn2054-5703
dc.identifier.urihttp://hdl.handle.net/11343/253452
dc.description.abstractControlling the behaviour of cells by rationally guiding molecular processes is an overarching aim of much of synthetic biology. Molecular processes, however, are notoriously noisy and frequently nonlinear. We present an approach to studying the impact of control measures on motifs of molecular interactions that addresses the problems faced in many biological systems: stochasticity, parameter uncertainty and nonlinearity. We show that our reachability analysis formalism can describe the potential behaviour of biological (naturally evolved as well as engineered) systems, and provides a set of bounds on their dynamics at the level of population statistics: for example, we can obtain the possible ranges of means and variances of mRNA and protein expression levels, even in the presence of uncertainty about model parameters.
dc.languageEnglish
dc.publisherROYAL SOC
dc.titleControl mechanisms for stochastic biochemical systems via computation of reachable sets
dc.typeJournal Article
dc.identifier.doi10.1098/rsos.160790
melbourne.affiliation.departmentSchool of BioSciences
melbourne.source.titleRoyal Society Open Science
melbourne.source.volume4
melbourne.source.issue8
dc.rights.licenseCC BY
melbourne.elementsid1365118
melbourne.contributor.authorStumpf, Michael
dc.identifier.eissn2054-5703
melbourne.accessrightsOpen Access


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