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dc.contributor.advisorDavid Gifford.en_US
dc.contributor.authorKang, Daniel Den_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2016-12-22T16:29:41Z
dc.date.available2016-12-22T16:29:41Z
dc.date.copyright2015en_US
dc.date.issued2015en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/106117
dc.descriptionThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages [18]-[20]).en_US
dc.description.abstractWe introduce a new model called CCM+ that rectifies the inability of previous sequence-based methods to generalize across cell-types. We permit generalization by introducing arbitrary base-pair resolution covariates. We show that the addition of base-pair resolution chromatin accessibility covariate greatly aids in the prediction of cis-regulatory marks. Additionally, we show that by using cell-type specific covariates, CCM+ can generalize across cell-types. Finally, we show CCM+ can be used for downstream analysis that matches state-of-the-art methods when chromatin accessibility is used as a covariate.en_US
dc.description.statementofresponsibilityby Daniel Kang.en_US
dc.format.extent27 unnumbered pagesen_US
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/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleExploring cis-regulatory models of the genome to predict epigenetic state and variationen_US
dc.typeThesisen_US
dc.description.degreeM. Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc965798517en_US


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