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dc.contributor.authorBarker, Brandonen_US
dc.date.accessioned2015-01-07T20:56:59Z
dc.date.available2019-08-19T06:01:03Z
dc.date.issued2014-08-18en_US
dc.identifier.otherbibid: 8793246
dc.identifier.urihttps://hdl.handle.net/1813/38758
dc.description.abstractQuantitative models are increasingly being used to interrogate the metabolic pathways that are contained within complex biological processes, and at a higher level, these models are used to explore questions in evolution with complex physiological processes absent in typical, idealized population genetic models. In this work, we focus both on the application of quantitative models in evolution and the development of new quantitative methods for metabolism. An overview of constraint-based modeling and its purview in the field of metabolic modeling is given in Chapter 1. By using a simple version of constraint-based modeling known as flux balance analysis (FBA), we elucidate patterns that occur in gene-gene interactions of deleterious mutations (Chapters 2 and 3). Because many biological problems relate to systems that are not well-suited to FBA, especially when establishing a physiologically accurate flux is desirable, we address the problem of estimating metabolic fluxes using constraint-based models and readily available gene expression data by developing a new methodology and software (called FALCON; Chapter 4). We then take advantage of the FALCON method by using it in the development of approaches that enable the simulation of beneficial mutations and reveal some of the influences that metabolic networks bring to bear on the study of adaptation (Chapter 5).en_US
dc.language.isoen_USen_US
dc.subjectmetabolic modelingen_US
dc.subjectsystems biologyen_US
dc.subjectflux balance analysisen_US
dc.titleAdvances In Genome-Scale Modeling Applied To Expression-Based Flux Estimation And Epistasis Predictionen_US
dc.typedissertation or thesisen_US
thesis.degree.disciplineComputational Biology
thesis.degree.grantorCornell Universityen_US
thesis.degree.levelDoctor of Philosophy
thesis.degree.namePh. D., Computational Biology
dc.contributor.chairGu, Zhenglongen_US
dc.contributor.committeeMemberChristini, Daviden_US
dc.contributor.committeeMemberMyers, Christopher Ren_US
dc.contributor.committeeMemberStillman, Michael Eugeneen_US


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