Date of Award


Degree Type


Degree Name


Degree Program

Engineering and Applied Science


Computer Science

Major Professor

Taylor, Christopher

Second Advisor

Bilar, Daniel

Third Advisor

Chen, Huimin

Fourth Advisor

Summa, Christopher

Fifth Advisor

Ferris, Michael


Microbes are the most abundant and most diverse form of life on Earth, constituting the largest portion of the total biomass of the entire planet. They are present in every niche in nature, including very extreme environments, and they govern biogeochemical transformations in ecosystems. The human body is home to a diverse assemblage of microbial species as well. In fact, the number of microbial cells in the gastrointestinal tract, oral cavity, skin, airway passages and urogenital system is approximately an order of magnitude greater than the number of cells that make up the human body itself, and changes in the composition and relative abundance of these microbial communities are highly associated with intestinal and respiratory disorders and diseases of the skin and mucus membranes. In the early 1990's, cultivation-­‐independent methods, especially those based on PCR-­‐amplification and sequences of phylogenetically informative 16S rRNA genes, made it possible to assess the composition of microbial species in natural environments, advances in high-­‐throughput sequencing technologies in recent years have increased sequencing capacity and microbial detection by orders of magnitude. However, the effectiveness of current computational methods available to analyze the vast amounts of sequence data is poor and investigating the diversity within microbial communities remains challenging. In addition to offering an easy-­‐to-­‐use visualization and statistical analysis framework for microbial community analyses, the study described herein aims to present a biologically relevant computational approach for assessing microbial diversity at finer scales of microbial communities through nucleotide variation in 16S rRNA genes.


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