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Advances In Genome-Scale Modeling Applied To Expression-Based Flux Estimation And Epistasis Prediction

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Abstract

Quantitative 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).

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2014-08-18

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metabolic modeling; systems biology; flux balance analysis

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Gu, Zhenglong

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Christini, David
Myers, Christopher R
Stillman, Michael Eugene

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Computational Biology

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Ph. D., Computational Biology

Degree Level

Doctor of Philosophy

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Government Document

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dissertation or thesis

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