Evolving Local Minima in the Protein Energy Surface

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dc.contributor.advisorShehu, Amarda
dc.contributor.authorOlson, Brian Steffel
dc.creatorOlson, Brian Steffel
dc.date.accessioned2013-08-19T21:16:50Z
dc.date.available2013-08-19T21:16:50Z
dc.date.issued2013-08
dc.description.abstractProteins are the molecular tools of living cells and the path to unraveling their function is through modeling and understanding their structure. Many diseases occur when a protein loses its intended function due to inability to form the appropriate structure with which it binds to other molecules. A holistic approach to protein modeling would characterize all possible structural states accessible by a protein under native conditions. However, this task is infeasible. The question then becomes, how can we model the subset of these structural states most relevant to the function or disfunction of a protein?
dc.format.extent154 pages
dc.identifier.urihttps://hdl.handle.net/1920/8371
dc.language.isoen
dc.rightsCopyright 2013 Brian Steffel Olson
dc.subjectComputer science
dc.subjectBioinformatics
dc.subjectEvolutionary Computation
dc.subjectNative Conformation
dc.subjectProtein Structure Prediction
dc.subjectStochastic Search
dc.titleEvolving Local Minima in the Protein Energy Surface
dc.typeDissertation
thesis.degree.disciplineComputer Science
thesis.degree.grantorGeorge Mason University
thesis.degree.levelDoctoral

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