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Title page for ETD etd-05282008-161200


Type of Document Master's Thesis
Author Durham, Elizabeth Ashley
URN etd-05282008-161200
Title Knowledge-based environment potentials for protein structure prediction
Degree Master of Science
Department Biomedical Informatics
Advisory Committee
Advisor Name Title
Jens Meiler Committee Chair
Dan Masys Committee Member
Dave Tabb Committee Member
Keywords
  • Proteins -- Structure
  • knowlege-based potential
  • solvent-accessible surface area
  • protein structure prediction
  • environment free energy
  • Computer algorithms
  • Proteins -- Surfaces
Date of Defense 2008-05-12
Availability unrestricted
Abstract
This Master’s Thesis project had as its objectives: (1) to optimize algorithms for solvent-accessible surface area (SASA) approximation to develop an environment free energy knowledge-based potential; and, (2) to assess the knowledge-based environment free energy potentials for de novo protein structure prediction. This project achieved its goals by developing, implementing, optimizing, and evaluating four different algorithms for approximating the SASA of a given protein model and generating knowledge-based potentials for de novo protein structure prediction. The algorithms are entitled Neighbor Count, Neighbor Vector, Artificial Neural Network, and Overlapping Spheres.
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