Microorganisms are key players in the ecosystem functioning. In this thesis, we developed a framework to preprocess raw microbiome data, build a correlation network, and analyze co-occurrence patterns between microbes. We then applied this framework to a marine microbiome dataset. The dataset used in this study comes from a year-long time-series to characterize the microbial communities in our coastal waters off the Cal Poly Pier. In analyzing this dataset, we were able to observe and confirm previously discovered patterns of interactions and generate hypotheses about new patterns. The analysis of co-occurrences between prokaryotic and eukaryotic taxa is relatively novel and can provide new insight into how marine microbial communites are structured and interact.
","abstract_html":"<p>Microorganisms are key players in the ecosystem functioning. In this thesis, we developed a framework to preprocess raw microbiome data, build a correlation network, and analyze co-occurrence patterns between microbes. We then applied this framework to a marine microbiome dataset. The dataset used in this study comes from a year-long time-series to characterize the microbial communities in our coastal waters off the Cal Poly Pier. In analyzing this dataset, we were able to observe and confirm previously discovered patterns of interactions and generate hypotheses about new patterns. The analysis of co-occurrences between prokaryotic and eukaryotic taxa is relatively novel and can provide new insight into how marine microbial communites are structured and interact.</p>","abstract_has_math":false,"creators":["Nguyen, Lien Viet"],"institution":null,"degree_name":"MS in Computer Science","degree_level":null,"degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Theresa Migler","Computer Science","College of Engineering"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-07-01T07:00:00Z","date_published":"2021-07-01T07:00:00Z","updated_at":"2026-07-24T01:32:50Z","subjects":["Graph Theory","Microbiome","Other Computer Sciences","Terrestrial and Aquatic Ecology"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["10.15368/theses.2021.121"],"render_values":[{"text":"10.15368/theses.2021.121","href":"https://doi.org/10.15368/theses.2021.121","code":true}]}]},"links":{"outbound_url":"https://digitalcommons.calpoly.edu/theses/2588","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Theresa Migler","Computer Science","College of Engineering"]},{"key":"dc:creator","label":"Author","values":["Nguyen, Lien Viet"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2021-07-28T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS in Computer Science"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Graph Theory","Microbiome","Other Computer Sciences","Terrestrial and Aquatic Ecology"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.calpoly.edu/theses/2588","10.15368/theses.2021.121"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Microorganisms are key players in the ecosystem functioning. In this thesis, we developed a framework to preprocess raw microbiome data, build a correlation network, and analyze co-occurrence patterns between microbes. We then applied this framework to a marine microbiome dataset. The dataset used in this study comes from a year-long time-series to characterize the microbial communities in our coastal waters off the Cal Poly Pier. In analyzing this dataset, we were able to observe and confirm previously discovered patterns of interactions and generate hypotheses about new patterns. The analysis of co-occurrences between prokaryotic and eukaryotic taxa is relatively novel and can provide new insight into how marine microbial communites are structured and interact.
"]},{"key":"dc:title","label":"Title","values":["Analysis of the SLO Bay Microbiome from a Network Perspective"]}]}],"canonical_facts":{"dc:contributor":["Theresa Migler","Computer Science","College of Engineering"],"dc:creator":["Nguyen, Lien Viet"],"dc:date.available":["2021-07-28T07:00:00Z"],"dc:description.abstract":["Microorganisms are key players in the ecosystem functioning. In this thesis, we developed a framework to preprocess raw microbiome data, build a correlation network, and analyze co-occurrence patterns between microbes. We then applied this framework to a marine microbiome dataset. The dataset used in this study comes from a year-long time-series to characterize the microbial communities in our coastal waters off the Cal Poly Pier. In analyzing this dataset, we were able to observe and confirm previously discovered patterns of interactions and generate hypotheses about new patterns. The analysis of co-occurrences between prokaryotic and eukaryotic taxa is relatively novel and can provide new insight into how marine microbial communites are structured and interact.
"],"dc:identifier":["https://digitalcommons.calpoly.edu/theses/2588","10.15368/theses.2021.121"],"dc:subject":["Graph Theory","Microbiome","Other Computer Sciences","Terrestrial and Aquatic Ecology"],"dc:title":["Analysis of the SLO Bay Microbiome from a Network Perspective"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_name":["MS in Computer Science"]},"updated_at":"2026-07-24T01:32:50Z"}