Applied bioinformatics for exploring diversity patterns in meta-omic data

This thesis explores the utility of applied bioinformatic approaches to better understand sequence space and phylogenetic diversity in meta-omic clinical and environmental datasets. In three chapters, the thesis describes how applied bioinformatic techniques can be used to 1) identify and quantify s...

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Bibliographic Details
Main Author: Ranjan, Piyush
Other Authors: Stewart, Frank J., Biology, Glass, Jennifer B., Choi, Jung H.
Format: Thesis
Language:English
Published: Georgia Institute of Technology 2018
Subjects:
Online Access:http://hdl.handle.net/1853/59947
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spelling ftgeorgiatech:oai:smartech.gatech.edu:1853/59947 2023-05-15T17:11:58+02:00 Applied bioinformatics for exploring diversity patterns in meta-omic data Ranjan, Piyush Stewart, Frank J. Biology Glass, Jennifer B. Choi, Jung H. 2018-05-31T18:17:23Z application/pdf http://hdl.handle.net/1853/59947 en_US eng Georgia Institute of Technology http://hdl.handle.net/1853/59947 Bioinformatics CRISPR Oxygen minimum zone Atribacteria Text Thesis 2018 ftgeorgiatech 2023-01-30T18:41:24Z This thesis explores the utility of applied bioinformatic approaches to better understand sequence space and phylogenetic diversity in meta-omic clinical and environmental datasets. In three chapters, the thesis describes how applied bioinformatic techniques can be used to 1) identify and quantify sequence variation in the form of insertions and deletions generated as an effect of off-target activity by CRISPR-Cas9 nuclease using high throughput targeted gene amplicon sequencing; 2) identify and quantify the abundance of elements of the bacterial defense systems, CRISPRs, to explore viral-microbe interaction dynamics in natural microbial communities living in marine oxygen minimum zones using high-throughput metagenome sequencing; and 3) investigate phylogenetic variation in an underexplored phylum of bacteria, Atribacteria, that are found as dominant members of microbial communities in methane hydrate-bearing marine sediments again using high-throughput metagenome sequencing. M.S. Thesis Methane hydrate Georgia Institute of Technology: SMARTech - Scholarly Materials and Research at Georgia Tech
institution Open Polar
collection Georgia Institute of Technology: SMARTech - Scholarly Materials and Research at Georgia Tech
op_collection_id ftgeorgiatech
language English
topic Bioinformatics
CRISPR
Oxygen minimum zone
Atribacteria
spellingShingle Bioinformatics
CRISPR
Oxygen minimum zone
Atribacteria
Ranjan, Piyush
Applied bioinformatics for exploring diversity patterns in meta-omic data
topic_facet Bioinformatics
CRISPR
Oxygen minimum zone
Atribacteria
description This thesis explores the utility of applied bioinformatic approaches to better understand sequence space and phylogenetic diversity in meta-omic clinical and environmental datasets. In three chapters, the thesis describes how applied bioinformatic techniques can be used to 1) identify and quantify sequence variation in the form of insertions and deletions generated as an effect of off-target activity by CRISPR-Cas9 nuclease using high throughput targeted gene amplicon sequencing; 2) identify and quantify the abundance of elements of the bacterial defense systems, CRISPRs, to explore viral-microbe interaction dynamics in natural microbial communities living in marine oxygen minimum zones using high-throughput metagenome sequencing; and 3) investigate phylogenetic variation in an underexplored phylum of bacteria, Atribacteria, that are found as dominant members of microbial communities in methane hydrate-bearing marine sediments again using high-throughput metagenome sequencing. M.S.
author2 Stewart, Frank J.
Biology
Glass, Jennifer B.
Choi, Jung H.
format Thesis
author Ranjan, Piyush
author_facet Ranjan, Piyush
author_sort Ranjan, Piyush
title Applied bioinformatics for exploring diversity patterns in meta-omic data
title_short Applied bioinformatics for exploring diversity patterns in meta-omic data
title_full Applied bioinformatics for exploring diversity patterns in meta-omic data
title_fullStr Applied bioinformatics for exploring diversity patterns in meta-omic data
title_full_unstemmed Applied bioinformatics for exploring diversity patterns in meta-omic data
title_sort applied bioinformatics for exploring diversity patterns in meta-omic data
publisher Georgia Institute of Technology
publishDate 2018
url http://hdl.handle.net/1853/59947
genre Methane hydrate
genre_facet Methane hydrate
op_relation http://hdl.handle.net/1853/59947
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