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Data Mining Framework For Metagenome Analysis

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dc.contributor.advisor Rangwala, Huzefa
dc.contributor.author Rasheed, Zeehasham
dc.creator Rasheed, Zeehasham en_US
dc.date.accessioned 2013-08-09T15:40:05Z
dc.date.available 2013-08-09T15:40:05Z
dc.date.issued 2013 en_US
dc.identifier.uri https://hdl.handle.net/1920/8285
dc.description.abstract Advances in biotechnology have dramatically changed the manner of characterizing large populations of microbial communities that are ubiquitous across several environments. The process of "metagenomics" involves sequencing of the genetic material of organisms co-existing within ecosystems ranging from ocean, soil and human body. Researchers are trying to determine the collective microbial community or population of microbes that co-exist across different environmental and clinical samples. Several researchers and clinicians have embarked on studying the pathogenic role played by the microbiome (i.e., the collection of microbial organisms within the human body) with respect to human health and disease conditions.
dc.format.extent 143 pages en_US
dc.language.iso en en_US
dc.rights Copyright 2013 Zeehasham Rasheed en_US
dc.subject Computer science en_US
dc.subject Bioinformatics en_US
dc.subject Bioinformatics en_US
dc.subject Clustering and Classification en_US
dc.subject Data Mining en_US
dc.subject Hashing en_US
dc.subject Machine Learning en_US
dc.subject Metagenomics en_US
dc.title Data Mining Framework For Metagenome Analysis en_US
dc.type Dissertation en
thesis.degree.level Doctoral en
thesis.degree.discipline Computer Science en
thesis.degree.grantor George Mason University en


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