With the ever increasing amount of high-throughput molecular profile data, biologists need versatile tools to enable them to quickly and succinctly analyze their data. Furthermore, pathway databases have grown increasingly robust with the KEGG database at the forefront. Previous tools have color-coded the genes on different pathways using differential expression analysis. Unfortunately, they do not adequately capture the relationships of the genes amongst one another. Structure Enrichment Analysis (SEA) thus seeks to take biological analysis to the next level. SEA accomplishes this goal by highlighting for users the sub-pathways of a biological pathways that best correspond to their molecular profile data in an easy to use GUI interface.
","abstract_html":"<p> <p>With the ever increasing amount of high-throughput molecular profile data, biologists need versatile tools to enable them to quickly and succinctly analyze their data. Furthermore, pathway databases have grown increasingly robust with the KEGG database at the forefront. Previous tools have color-coded the genes on different pathways using differential expression analysis. Unfortunately, they do not adequately capture the relationships of the genes amongst one another. Structure Enrichment Analysis (SEA) thus seeks to take biological analysis to the next level. SEA accomplishes this goal by highlighting for users the sub-pathways of a biological pathways that best correspond to their molecular profile data in an easy to use GUI interface.</p> </p> <p> <p> <p> <p> <p> <p> <p> <p> </p> </p> </p> </p> </p> </p> </p> </p> <p> <p> <p> <p> <p> <p> <p> </p> </p> </p> </p> </p> </p> </p> <p> <p> <p> <p> <p> <p> </p> </p> </p> </p> </p> </p> <p> <p> <p> <p> <p> </p> </p> </p> </p> </p> <p> <p> <p> <p> </p> </p> </p> </p> <p> <p> <p> </p> </p> </p> <p> <p> </p> </p> <p> </p>","abstract_has_math":false,"creators":["Judeh, Thair"],"institution":null,"degree_name":"M.S.","degree_level":"Thesis-Restricted","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Zhu, Dongxiao","Summa, Christopher M.","DePano, Nathanael A."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-08-04T07:00:00Z","date_published":"2011-08-04T07:00:00Z","updated_at":"2026-07-24T05:28:10Z","subjects":["Network Partitioning, Network Reconstruction, Structure Enrichment Analysis, Community","Computer Sciences"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarworks.uno.edu/td/463","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Zhu, Dongxiao","Summa, Christopher M.","DePano, Nathanael A."]},{"key":"dc:creator","label":"Author","values":["Judeh, Thair"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis-Restricted"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Network Partitioning, Network Reconstruction, Structure Enrichment Analysis, Community","Computer Sciences"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarworks.uno.edu/td/463"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["
With the ever increasing amount of high-throughput molecular profile data, biologists need versatile tools to enable them to quickly and succinctly analyze their data. Furthermore, pathway databases have grown increasingly robust with the KEGG database at the forefront. Previous tools have color-coded the genes on different pathways using differential expression analysis. Unfortunately, they do not adequately capture the relationships of the genes amongst one another. Structure Enrichment Analysis (SEA) thus seeks to take biological analysis to the next level. SEA accomplishes this goal by highlighting for users the sub-pathways of a biological pathways that best correspond to their molecular profile data in an easy to use GUI interface.
"]},{"key":"dc:title","label":"Title","values":["SEA: a novel computational and GUI software pipeline for detecting activated biological sub-pathways"]}]}],"canonical_facts":{"dc:contributor":["Zhu, Dongxiao","Summa, Christopher M.","DePano, Nathanael A."],"dc:creator":["Judeh, Thair"],"dc:description.abstract":["
With the ever increasing amount of high-throughput molecular profile data, biologists need versatile tools to enable them to quickly and succinctly analyze their data. Furthermore, pathway databases have grown increasingly robust with the KEGG database at the forefront. Previous tools have color-coded the genes on different pathways using differential expression analysis. Unfortunately, they do not adequately capture the relationships of the genes amongst one another. Structure Enrichment Analysis (SEA) thus seeks to take biological analysis to the next level. SEA accomplishes this goal by highlighting for users the sub-pathways of a biological pathways that best correspond to their molecular profile data in an easy to use GUI interface.
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