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dc.contributor.advisorXu, Dong, 1965-eng
dc.contributor.authorZhang, Chaoeng
dc.date.issued2012eng
dc.date.submitted2012 Summereng
dc.descriptionTitle from PDF of title page (University of Missouri--Columbia, viewed on July 30, 2013).eng
dc.descriptionThe entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.eng
dc.descriptionDissertation advisor: Dr. Dong Xueng
dc.descriptionIncludes bibliographical references.eng
dc.descriptionVita.eng
dc.descriptionPh. D. University of Missouri--Columbia 2012.eng
dc.description"July 2012"eng
dc.description.abstractWith the rapid development of next-generation sequencing technologies, bacterial identification becomes a very important and essential step in processing genomic data, especially for metagenomic data. Many computational methods have been developed and some of them are widely used to address the problems in bacterial identification. First we review the algorithms of these methods, discuss their drawbacks, and propose future computational methods that use genomic data to characterize bacteria. Then, we tackle two specific computational problems in bacterial identification, namely, the detection of host-specific bacteria and the detection of disease-associated bacteria, by offering potential solutions as a starting point for those who are interested in the area. In addition, by utilizing our knowledge of H. pylori, we also predicted novel effectors for those known pathogens.eng
dc.description.bibrefIncludes bibliographical referenceseng
dc.format.extentviii, 115 pageseng
dc.identifier.oclc872569096eng
dc.identifier.urihttps://doi.org/10.32469/10355/36756eng
dc.identifier.urihttps://hdl.handle.net/10355/36756
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcommunityUniversity of Missouri--Columbia. Graduate School. Theses and Dissertations.eng
dc.rightsOpenAccesseng
dc.rights.licenseThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.
dc.subjectbacterial identificationeng
dc.subjectcomputational methodseng
dc.subjectgenomic dataeng
dc.titleComputational methods for bacterial characterization and bacteria-host/environment interaction analyseseng
dc.typeThesiseng
thesis.degree.disciplineComputer science (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelDoctoraleng
thesis.degree.namePh. D.eng


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