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dc.contributor.advisorTomaso Poggio.en_US
dc.contributor.authorSoni, Nehaen_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2007-01-10T16:47:32Z
dc.date.available2007-01-10T16:47:32Z
dc.date.copyright2006en_US
dc.date.issued2006en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/35608
dc.descriptionThesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.en_US
dc.descriptionIncludes bibliographical references (p. 53-55).en_US
dc.description.abstractAlternative splicing plays a major role in protein diversity and regulating gene expression. Motifs that regulate tissue-specific alternative splicing have been identified by groups studying small sets of genes. We introduce a tissue-specific skipping score for skipped exons using exon-exon junction microarray data. We compare these exons with known literature-verified EST skipped exons and exons predicted to be skipped in both human and mouse. After deriving tissue-specific skipped exon sets for brain, heart, muscle and testis, we find sequence features in the exon and flanking introns that distinguish these tissue-specific skipped exons from constitutive exons. Lastly, we use sequence-based scoring based on these features to predict tissue-specific skipped exons and compare these with EST data to demonstrate the tissue-specificity of the motifs.en_US
dc.description.statementofresponsibilityby Neha Soni.en_US
dc.format.extent55 p.en_US
dc.format.extent2331125 bytes
dc.format.extent2445564 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleSequence motifs predictive of tissue-specific skippingen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc75285176en_US


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