{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/81717"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/81717","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Methods for Cluster Analysis and Validation in Microarray Gene Expression Data","abstract":"U of I Only","abstract_html":"U of I Only","abstract_has_math":false,"creators":["Kosorukoff, Alexander Lvovich"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Sylvian Ray"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-25T20:20:08Z","date_published":"2015-09-25T20:20:08Z","updated_at":"2026-07-22T22:26:16Z","subjects":["Biology, Bioinformatics"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3223632"],"render_values":[{"text":"(MiAaPQ)AAI3223632","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/81717","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Sylvian Ray"]},{"key":"dc:creator","label":"Author","values":["Kosorukoff, Alexander Lvovich"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-25T20:20:08Z","10000-01-01","2006"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Biology, Bioinformatics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/81717","(MiAaPQ)AAI3223632"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["U of I Only","Results. We evaluate this method using both artificial and yeast microarray data. By choosing parameters settings that minimize FCS values and maximize CS values we show major advantages over other clustering methods in particular for identifying combinatorially regulated groups of genes. The results produced provide remarkable enrichment for cis-regulatory elements in clusters of genes known to be regulated by such elements and evidence of extensive combinatorial regulation. Moreover, the method can be generalized when prior information about cis-regulatory sites is absent or it is desirable to calculate FCS values based on functional categorization.","103 p.","Made available in DSpace on 2015-09-25T20:20:08Z (GMT). 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