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dc.contributor.advisorHahn, Juergen
dc.creatorBansal, Loveleena
dc.date.accessioned2014-05-13T17:27:02Z
dc.date.available2015-12-01T06:31:21Z
dc.date.created2013-12
dc.date.issued2013-12-10
dc.date.submittedDecember 2013
dc.identifier.urihttps://hdl.handle.net/1969.1/151856
dc.description.abstractBuilding quantitative models of biological systems is a challenging task as these models can consist of a very large number of components with complex interactions between them and the experimental data available for model validation is often sparse and noisy. The focus in this work is on modeling and parameter estimation of biological systems that are monitored using fluorescent reporter systems. Fluorescent reporter systems are widely used for various applications such as monitoring gene expression, protein localization and protein-protein interactions. This dissertation presents various techniques to facilitate modeling of biological systems containing fluorescent reporters with special attention given to challenges arising due to limited experimental data, simultaneous monitoring of multiple events and variability in the observed response due to phenotypic differences. First, an inverse problem is formulated to estimate the dynamics of transcription factors, a crucial molecule that initiates the transcription process, using data of fluorescence intensity profiles obtained from a fluorescent reporter system. The resulting inverse problem is ill-conditioned and it is solved with the aid of regularization techniques. The main contribution is that, with the presented technique, any complex dynamics of transcription factors can be estimated using limited data of fluorescence measurements. The technique has been evaluated using simulated data as well as experimental data of a GFP reporter system of STAT3. Second, an experimental design formulation is developed to facilitate the use of multiple fluorescent reporters, with overlapping emission spectra, in the same experiment. This work develops a criterion to select the fluorescent proteins for simultaneous use such that the accuracy in the estimated contributions of individual proteins to the overall observed intensity is maximized. This technique has been validated using mixtures of different E. coli strains which express different fluorescent proteins. Finally, a population balance model of a cell population containing a fluorescence reporter system is developed to describe the variability in the observed fluorescence in cells. Factors such as rate of fluorescent protein formation as well as partitioning of the fluorescent protein on cell division have been taken into account to describe the dynamics of fluorescence intensity distributions in the cell populations. The model has been used to obtain preliminary hypotheses to explain the difference in response of HeLa cells containing the Tet-on expression system on stimulation by different levels doxycycline. Thus, this work describes techniques for building robust predictive models of biological systems such as regularization for solving ill-posed estimation problems, experimental design techniques as well as using population balance modeling to model complex multi-scale dynamics. Moreover, while the examples discussed here are motivated for fluorescent reporter systems, the developed techniques can be used for different kinds of linear or non-linear dynamic biological systems.en
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.subjectSystems Biologyen
dc.subjectMathematical Modelingen
dc.subjectFluorescent Reporteren
dc.subjectInverse Problemsen
dc.subjectRegularizationen
dc.subjectExperimental Designen
dc.subjectD-Optimality Criterionen
dc.subjectPopulation Balance Modelingen
dc.subjectSensitivity Analysisen
dc.subjectFinite Differenceen
dc.titleQuantitative Modeling and Estimation in Systems Biology using Fluorescent Reporter Systemsen
dc.typeThesisen
thesis.degree.departmentChemical Engineeringen
thesis.degree.disciplineChemical Engineeringen
thesis.degree.grantorTexas A & M Universityen
thesis.degree.nameDoctor of Philosophyen
thesis.degree.levelDoctoralen
dc.contributor.committeeMemberLaird, Carl
dc.contributor.committeeMemberJayaraman, Arul
dc.contributor.committeeMemberRasmussen, Bryan
dc.type.materialtexten
dc.date.updated2014-05-13T17:27:02Z
local.embargo.terms2015-12-01


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