{"id":{"repo_id":"wustl","oai_identifier":"oai:openscholarship.wustl.edu:etd-1445"},"canonical_url":"https://search.dev.ndltd.org/etd/wustl/oai:openscholarship.wustl.edu:etd-1445","repository":{"repo_id":"wustl","name":"Washington University in St. Louis","base_url":"https://openscholarship.wustl.edu/do/oai/"},"display":{"title":"Clinical Interpretation of Novel Copy Number Variations","abstract":"Copy Number Variations: CNVs) are a significant source of human genetic diversity and are believed to be responsible for a wide variety of phenotypic variation. Recent advances in microarray-based genomic hybridization techniques have facilitated CNV analysis as a viable diagnostic technique in the clinic, and several public databases of well-characterized CNVs are being compiled, but a standard for interpreting uncharacterized CNVs has yet to emerge. This thesis examines the clinical interpretation of uncharacterized CNVs as a multiple instance binary classification problem. 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Recent advances in microarray-based genomic hybridization techniques have facilitated CNV analysis as a viable diagnostic technique in the clinic, and several public databases of well-characterized CNVs are being compiled, but a standard for interpreting uncharacterized CNVs has yet to emerge. This thesis examines the clinical interpretation of uncharacterized CNVs as a multiple instance binary classification problem. We analyze the current state of clinical techniques, then present and test several novel statistical approaches to the problem."]},{"key":"dc:title","label":"Title","values":["Clinical Interpretation of Novel Copy Number Variations"]}]}],"canonical_facts":{"dc:contributor":["S. Swamidass"],"dc:creator":["Carey, Clifton"],"dc:date.available":["2010-01-01T08:00:00Z"],"dc:description.abstract":["Copy Number Variations: CNVs) are a significant source of human genetic diversity and are believed to be responsible for a wide variety of phenotypic variation. Recent advances in microarray-based genomic hybridization techniques have facilitated CNV analysis as a viable diagnostic technique in the clinic, and several public databases of well-characterized CNVs are being compiled, but a standard for interpreting uncharacterized CNVs has yet to emerge. This thesis examines the clinical interpretation of uncharacterized CNVs as a multiple instance binary classification problem. We analyze the current state of clinical techniques, then present and test several novel statistical approaches to the problem."],"dc:identifier":["https://openscholarship.wustl.edu/etd/446"],"dc:identifier.doi":["https://doi.org/10.7936/K7CR5RDM"],"dc:language":["English (en)"],"dc:subject":["Computer Science"],"dc:title":["Clinical Interpretation of Novel Copy Number Variations"],"thesis:degree_discipline":["Computer Science and Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Arts (MA)"]},"updated_at":"2026-07-24T06:13:31Z"}