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Understanding and Analyzing the Human Microbiome: Taxonomic Identification and Potential Interactions

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dc.contributor.advisor Gillevet, Patrick M.
dc.contributor.author Naqvi, Arnmar S. Abbas
dc.creator Naqvi, Arnmar S. Abbas
dc.date 2010-01-13
dc.date.accessioned 2011-06-14T17:00:20Z
dc.date.available NO_RESTRICTION en_US
dc.date.available 2011-06-14T17:00:20Z
dc.date.issued 2011-06-14
dc.identifier.uri https://hdl.handle.net/1920/6411
dc.description.abstract The Microbiome Analysis Center, in collaboration with Rush University Medical Center and Case Western University, has been studying and characterizing gut microbiota in normal and diseased states such as ALD and HIV. Currently, the Multitag Pyrosequencing (MTPS) methodology developed by Dr. Gillevet is being used to inten-ogate the microbiome from dozens of samples at a time. As a result we have been receiving hundreds of samples of both bacterial and fungal microbiome of stool, mucosal biopsy, and oral samples from a large number of subjects and diseases. The vast volumes of data flowing from diverse sources has necessitated the development of analysis pipelines in order to intelligently and rapidly process the molecular information and to analyze, cluster, and con-elate the sample datasets. However, a fundamental and pre-requisite for most research in this particular is being able to efficiently and accurately identify the genus and species information given a set of SSU rRNA sequences. The cun-ent implementation of this type of investigation is widespread, but as datasets get very large it proves to be very impractical due to factors concerning run-time and memory. For this particular study, we have developed and designed a portable and robust tool to identify the bacterial taxonomy and distribution at the species level, specifically in patients with HIV looking at the vaginal microflora. Another very important aspect of the Microbiome is to understand the relationships of the bacteria between and amongst different classes (ie. healthy, diseased). In order to accomplish this we plan on applying a systems biology approach to the microflora. This study will produce an approach that will specifically look at the gut microbiota in relation to Alcohol Liver Disease at the graphical network level. A series of challenges is anticipated related to time and memory constraints, informative identification, and proper linkage of taxonomic identification to the clinical information in the microbiome. We discovered distinct and common features amongst our samples that will provide novel insights and ultimately broaden our understanding of how the microbiome influences human health, furthering future research in this rapidly progressing field.
dc.language.iso en_US en_US
dc.subject Microbiome en_US
dc.subject Bio Informatics en_US
dc.subject Taxonomic en_US
dc.title Understanding and Analyzing the Human Microbiome: Taxonomic Identification and Potential Interactions en_US
dc.type Thesis en
thesis.degree.name Masters in Bioinformatics and Computational Biology en_US
thesis.degree.level Master's en
thesis.degree.discipline Bioinformatics and Computational Biology en
thesis.degree.grantor George Mason University en


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