{"id":{"repo_id":"wustl","oai_identifier":"oai:openscholarship.wustl.edu:etd-1185"},"canonical_url":"https://search.dev.ndltd.org/etd/wustl/oai:openscholarship.wustl.edu:etd-1185","repository":{"repo_id":"wustl","name":"Washington University in St. Louis","base_url":"https://openscholarship.wustl.edu/do/oai/"},"display":{"title":"Novel Algorithms for Structural Alignment of Non-coding RNAs","abstract":"Non-coding RNAs are biologically important molecules, with a variety of catalytic and regulatory activities mediated by their secondary and tertiary structures. Base-pairing interactions, particularly at the secondary structure level, are an important tool for identifying and studying these structural RNAs, but also present some unique challenges for sequence analysis. Probabilistic covariance models are effective representations of structural RNAs, with generally high sensitivity and specificity but slow computational speed. New algorithms for dealing with structural RNAs are developed to address some of the practical deficiencies of covariance models. A new model of local alignment improves accuracy for fragmentary data, such as found in direct shotgun sequencing and metagenomic surveys. A separate and alternative model of local alignment is used as the basis for a structural search filter. This is combined with other filtering techniques and high-performance implementations to increase the practical speed of high-sensitivity search. As a whole, these improvements provide a foundation for and point toward future improvements in noncoding RNA homology search.","abstract_html":"Non-coding RNAs are biologically important molecules, with a variety of catalytic and regulatory activities mediated by their secondary and tertiary structures. Base-pairing interactions, particularly at the secondary structure level, are an important tool for identifying and studying these structural RNAs, but also present some unique challenges for sequence analysis. Probabilistic covariance models are effective representations of structural RNAs, with generally high sensitivity and specificity but slow computational speed. New algorithms for dealing with structural RNAs are developed to address some of the practical deficiencies of covariance models. A new model of local alignment improves accuracy for fragmentary data, such as found in direct shotgun sequencing and metagenomic surveys. A separate and alternative model of local alignment is used as the basis for a structural search filter. This is combined with other filtering techniques and high-performance implementations to increase the practical speed of high-sensitivity search. As a whole, these improvements provide a foundation for and point toward future improvements in noncoding RNA homology search.","abstract_has_math":false,"creators":["Kolbe, Diana"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation","degree_discipline":"Biology and Biomedical Sciences: Computational and Systems Biology","degree_department":null,"school":null,"contributors":["Sean Eddy"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2010,"date_issued":"2010-01-01T08:00:00Z","date_published":"2010-01-01T08:00:00Z","updated_at":"2026-07-24T06:13:49Z","subjects":["Biology","Bioinformatics","covariance model","genomics","noncoding RNA"],"languages":["English (en)"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.7936/K7CR5RC5"],"render_values":[{"text":"https://doi.org/10.7936/K7CR5RC5","href":"https://doi.org/10.7936/K7CR5RC5","code":true}]}]},"links":{"outbound_url":"https://openscholarship.wustl.edu/etd/186","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Sean Eddy"]},{"key":"dc:creator","label":"Author","values":["Kolbe, Diana"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2010-01-01T08:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Biology and Biomedical Sciences: Computational and Systems Biology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Biology","Bioinformatics","covariance model","genomics","noncoding RNA"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English (en)"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://openscholarship.wustl.edu/etd/186"]},{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.7936/K7CR5RC5"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Non-coding RNAs are biologically important molecules, with a variety of catalytic and regulatory activities mediated by their secondary and tertiary structures. Base-pairing interactions, particularly at the secondary structure level, are an important tool for identifying and studying these structural RNAs, but also present some unique challenges for sequence analysis. Probabilistic covariance models are effective representations of structural RNAs, with generally high sensitivity and specificity but slow computational speed. New algorithms for dealing with structural RNAs are developed to address some of the practical deficiencies of covariance models. A new model of local alignment improves accuracy for fragmentary data, such as found in direct shotgun sequencing and metagenomic surveys. A separate and alternative model of local alignment is used as the basis for a structural search filter. This is combined with other filtering techniques and high-performance implementations to increase the practical speed of high-sensitivity search. 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New algorithms for dealing with structural RNAs are developed to address some of the practical deficiencies of covariance models. A new model of local alignment improves accuracy for fragmentary data, such as found in direct shotgun sequencing and metagenomic surveys. A separate and alternative model of local alignment is used as the basis for a structural search filter. This is combined with other filtering techniques and high-performance implementations to increase the practical speed of high-sensitivity search. 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