An enumerative approach to computing cut sets in metabolic networks

dc.contributor.advisorChairperson, Graduate Committee: Brendan Mumeyen
dc.contributor.authorSalinas, Danielen
dc.date.accessioned2013-09-12T14:01:45Z
dc.date.available2013-09-12T14:01:45Z
dc.date.issued2013en
dc.description.abstractThe 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.urihttps://scholarworks.montana.edu/handle/1/2730en
dc.language.isoenen
dc.publisherMontana State University - Bozeman, College of Engineeringen
dc.rights.holderCopyright 2013 by Daniel Salinasen
dc.subject.lcshLinear programmingen
dc.subject.lcshGenetic programming (Computer science)en
dc.subject.lcshGenetic algorithmsen
dc.titleAn enumerative approach to computing cut sets in metabolic networksen
dc.typeThesisen
thesis.catalog.ckey2133847en
thesis.degree.committeemembersMembers, Graduate Committee: Jeffrey Heys; Mike Wittieen
thesis.degree.departmentComputer Science.en
thesis.degree.genreThesisen
thesis.degree.nameMSen
thesis.format.extentfirstpage1en
thesis.format.extentlastpage83en

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