An enumerative approach to computing cut sets in metabolic networks
dc.contributor.advisor | Chairperson, Graduate Committee: Brendan Mumey | en |
dc.contributor.author | Salinas, Daniel | en |
dc.date.accessioned | 2013-09-12T14:01:45Z | |
dc.date.available | 2013-09-12T14:01:45Z | |
dc.date.issued | 2013 | en |
dc.description.abstract | The productivity of organisms used in biotechnology may be enhanced when certain parts of their metabolism are rendered inaccessible. This can be achieved with genetic modifications, but current techniques set a practical limit on number of modifications that can be applied. Taking advantage of this limit, we implement a brute force algorithm that can compute cut sets for any set of metabolites and reactions that is shown to perform better than alternative approaches. Also, an attempt is made to approximate a binary linear program with a quadratic program; this approximation is meant to be used when refining the growth model of organisms used in flux balance analysis. The approximation is shown to be less efficient that the original program. Finally, extensions to the brute force algorithm are proposed. | en |
dc.identifier.uri | https://scholarworks.montana.edu/handle/1/2730 | en |
dc.language.iso | en | en |
dc.publisher | Montana State University - Bozeman, College of Engineering | en |
dc.rights.holder | Copyright 2013 by Daniel Salinas | en |
dc.subject.lcsh | Linear programming | en |
dc.subject.lcsh | Genetic programming (Computer science) | en |
dc.subject.lcsh | Genetic algorithms | en |
dc.title | An enumerative approach to computing cut sets in metabolic networks | en |
dc.type | Thesis | en |
thesis.catalog.ckey | 2133847 | en |
thesis.degree.committeemembers | Members, Graduate Committee: Jeffrey Heys; Mike Wittie | en |
thesis.degree.department | Computer Science. | en |
thesis.degree.genre | Thesis | en |
thesis.degree.name | MS | en |
thesis.format.extentfirstpage | 1 | en |
thesis.format.extentlastpage | 83 | en |
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