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dc.contributor.authorSubramaniam, Rajesh
dc.description.abstractViruses are unique organisms that lack the protein machinery necessary for its propagation (like polymerase) yet possess other proteins that facilitate its propagation (like host cell anchoring proteins). This study explores seven different frameworks to assist rapid visualization of proteins that are common to viruses residing in a given host. The proposed frameworks rely only on protein sequence information. It was found that the sequence similarity-based framework with an associated profile hidden Markov model was a better tool to assist visualization of proteins common to a given host than other proposed frameworks based only on amino acid composition or other amino acid properties. The lack of knowledge of profile hidden Markov models for many protein structures limit the utility of the proposed protein sequence similarity-based framework. The study concludes with an attempt to extrapolate the utility of the proposed framework to predict viruses that may pose potential human health risks.en_US
dc.publisherNorth Dakota State Universityen_US
dc.rightsNDSU policy 190.6.2en_US
dc.titleExploring Frameworks for Rapid Visualization of Viral Proteins Common for a Given Hosten_US
dc.typeThesisen_US
dc.date.accessioned2021-01-14T18:41:12Z
dc.date.available2021-01-14T18:41:12Z
dc.date.issued2019
dc.identifier.urihttps://hdl.handle.net/10365/31716
dc.subjectcommon proteinsen_US
dc.subjectdata miningen_US
dc.subjectdrug developmenten_US
dc.subjectpfamen_US
dc.subjectsequence similarityen_US
dc.subjectvirusesen_US
dc.identifier.orcid0000-0002-3757-1849
dc.rights.urihttps://www.ndsu.edu/fileadmin/policy/190.pdfen_US
ndsu.degreeMaster of Science (MS)en_US
ndsu.collegeEngineeringen_US
ndsu.departmentComputer Scienceen_US
ndsu.advisorDenton, Anne


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