Delayed stochastic modelling of prokaryotic transcription with abortive initiation

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dc.contributor.authorSharma, Silky
dc.contributor.authorUniversity of Lethbridge. Faculty of Arts and Science
dc.contributor.supervisorRoussel, Marc R.
dc.date.accessioned2017-03-20T16:03:37Z
dc.date.available2017-03-20T16:03:37Z
dc.date.issued2017
dc.degree.levelMastersen_US
dc.description.abstractA quantitative model for gene transcription should treat two main features: stochastic fluctuations due to low copy numbers, and time delays resulting from the lengthy sequence of reactions that form the transcription process. Bratsun et al. (PNAS, 102(41):14593-14598, 2005) proposed an algorithm by which we can include both of these features. I have studied a delay stochastic model for RNA transcription including abortive initiation. This study focused on the parametric dependence of the mean stationary RNA concentration and of the rise time, i.e. the characteristic time taken to achieve the stationary concentrations. The mean RNA concentration depends on initiation, elongation, polymerase arrest and RNA degradation rates including delays associated with clearance of promoter and polymerase arrest. Rise time depends on initiation, polymerase arrest, termination and RNA degradation rates. I have developed an analytic theory of rise time based on the delayed mass-action formalism to validate the simulation results.en_US
dc.embargoNoen_US
dc.identifier.urihttps://hdl.handle.net/10133/4806
dc.language.isoen_USen_US
dc.proquest.subject0487en_US
dc.proquestyesYesen_US
dc.publisherLethbridge, Alta : University of Lethbridge, Dept. of Chemistry and Biochemistryen_US
dc.publisher.departmentDepartment of Chemistry and Biochemistryen_US
dc.publisher.facultyArts and Scienceen_US
dc.relation.ispartofseriesThesis (University of Lethbridge. Faculty of Arts and Science)en_US
dc.subjectabortive initiationen_US
dc.subjectdelay stochastic simulation modelen_US
dc.subjectprokaryotic transcriptionen_US
dc.subjectrise timeen_US
dc.subjectRNA polymerase arresten_US
dc.subjectstochastic simulationsen_US
dc.titleDelayed stochastic modelling of prokaryotic transcription with abortive initiationen_US
dc.typeThesisen_US
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