Mixed-effect modeling of codon usage

dc.contributor.advisorWilke, C. (Claus)en
dc.contributor.committeeMemberStolp, Chandler W.en
dc.creatorFeng, Shujuanen
dc.date.accessioned2011-02-22T16:53:17Zen
dc.date.available2011-02-22T16:53:17Zen
dc.date.available2011-02-22T16:53:29Zen
dc.date.issued2010-12en
dc.date.submittedDecember 2010en
dc.date.updated2011-02-22T16:53:29Zen
dc.descriptiontexten
dc.description.abstractLogistic mixed effects models are used to determine whether optimal codons associate with two specific properties of the expressed protein: solvent accessibility, aggregation propensity, or evolutionary conservation. Both random components and fixed structures in the models are decided by following certain selection procedures. More models are also developed by considering different factor combinations using the same selection procedure. The results show that evolutionary conservation is the most important factor for predicting for the optimal codon usage for most amino acids; aggregation propensity is also an important factor, and solvent accessibility is the least important factor for most amino acids.The results of this analysis are consistent with the previous literature, provide more straightforward way to study the research question and also more information for the insight relationships.en
dc.description.departmentStatisticsen
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttp://hdl.handle.net/2152/ETD-UT-2010-12-2234en
dc.language.isoengen
dc.subjectLogistic mixed effectsen
dc.subjectModel selection proceduresen
dc.subjectOptimal codon usageen
dc.titleMixed-effect modeling of codon usageen
dc.type.genrethesisen
thesis.degree.departmentStatisticsen
thesis.degree.disciplineStatisticsen
thesis.degree.grantorUniversity of Texas at Austinen
thesis.degree.levelMastersen
thesis.degree.nameMaster of Science in Statisticsen

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