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dc.contributor.advisorAmy E. Keating.en_US
dc.contributor.authorGrigoryan, Gevorg, Ph. D. Massachusetts Institute of Technologyen_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Biology.en_US
dc.date.accessioned2007-09-28T13:29:45Z
dc.date.available2007-09-28T13:29:45Z
dc.date.copyright2007en_US
dc.date.issued2007en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/38997
dc.descriptionThesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biology, 2007.en_US
dc.descriptionIncludes bibliographical references (leaves 167-187).en_US
dc.description.abstractThere is a large class of applications in computational structural biology for which atomic-level representation is crucial for understanding the underlying biological phenomena, yet explicit atomic-level modeling is computationally prohibitive. Computational protein design, homology modeling, protein interaction prediction, docking and structure recognition are among these applications. Models that are commonly applied to these problems combine atomic-level representation with assumptions and approximations that make them computationally feasible. In this thesis I focus on several aspects of this type of modeling, analyze its limitations, propose improvements and explore applications to the design and prediction of protein-protein interactions.en_US
dc.description.statementofresponsibilityby Gevorg Grigoryan.en_US
dc.format.extent187 leavesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582
dc.subjectBiology.en_US
dc.titleComputational approaches for the design and prediction of protein-protein interactionsen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biology
dc.identifier.oclc166428687en_US


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