Computational modeling of macromolecular structures
Abstract
The main purpose of the research in this dissertation is to propose computational methods to create atomic models for macromolecular protein complexes. Protein interactions have been studied extensively, both experimentally and computationally. While traditional high-throughput approaches are useful to create large sets of relationships between proteins, these models do not provide detailed information about the physical mechanisms that proteins use to perform their biological functions. In this study we target three objectives in this domain. First, to develop a method for multiple protein docking. Second, to use multiple protein docking as the basis for Electron Microscopy Fitting. Finally, to create an enhanced probabilistic framework to model macromolecular structures that uses varied feature sources, ranging from Electron Microscopy information to physicochemical properties of interacting proteins. The development of three separate computational methods is explained, each answering the challenges posed by the previous objectives.
Degree
Ph.D.
Advisors
Kihara, Purdue University.
Subject Area
Bioinformatics|Computer science
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