Engineering Commons^™

Predicting Enzyme Targets For Optimization Of Metabolic Networks Under Uncertainty, David Christopher Flowers

Masters Theses

Recently, ensemble modeling was applied to metabolic networks for the sake of predicting the effects of genetic manipulations on the observed phenotype of the system. The ensemble of models is generated from experimental wild-type flux data and screened using phenotypic data from gene overexpression and knockout experiments, leaving predictive models. The need for data from multiple genetic perturbation experiments is an inherent limitation to this approach. In this investigation, ensemble modeling is used alongside elementary mode analysis to attempt to predict those enzymatic perturbations that are most likely to result in an increase in a target yield and a target …