Advances In Computer Aided Protein Structure Determination From Sparse Cryo Electron Microscopy Data

dc.contributor.advisorDiMaio, Frank
dc.contributor.authorFrenz, Brandon Michael
dc.date.accessioned2018-01-20T00:58:47Z
dc.date.available2018-01-20T00:58:47Z
dc.date.issued2018-01-20
dc.date.submitted2017
dc.descriptionThesis (Ph.D.)--University of Washington, 2017
dc.description.abstractSingle-particle cryo-electron microscopy (cryoEM) has become a powerful tool for determining macromolecular structures. Thanks to recent advances in direct electron detectors and motion correction algorithms it can frequently deliver electron density maps in the range of 3-5Å resolution. To obtain as much atomic level detail of the structure as possible from this data an accurate atomic model must be built. This can be done manually however, it is laborious and error prone. To resolve this problem modelers have turned to computational tools which can make up for lack of experimental data. Here we describe several tools for modeling with sparse experimental data, including a novel sampling strategy for de novo model completion and a novel refinement strategy for glycans with near atomic resolution cryoEM and x-ray crystallography data.
dc.embargo.termsOpen Access
dc.format.mimetypeapplication/pdf
dc.identifier.otherFrenz_washington_0250E_18143.pdf
dc.identifier.urihttp://hdl.handle.net/1773/40847
dc.language.isoen_US
dc.rightsCC BY
dc.subjectComputational Protein Modeling
dc.subjectCryo electron microscopy
dc.subjectGlycans
dc.subjectProtein Refinement
dc.subjectRosetta
dc.subjectBiochemistry
dc.subject.otherBiological chemistry
dc.titleAdvances In Computer Aided Protein Structure Determination From Sparse Cryo Electron Microscopy Data
dc.typeThesis

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