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dc.contributor.advisorCheng, Jianlineng
dc.contributor.authorHighsmith, Max Richardeng
dc.date.issued2021eng
dc.date.submitted2021 Falleng
dc.description.abstractThis dissertation, submitted as a partial requirement for completion of the Doctorate of Philosophy, outlines the research performed by Max Highsmith in the BDM Lab. This work includes a functional expansion of a three-dimensional genome conformation database, the development of a novel, deep-learning based strategy for the enhancement of Hi-C data, The development of deep learning approach for domain identification using epigenetic features, and the development of a novel computational tool for 4D modeling of chromosome dynamics.eng
dc.description.bibrefIncludes bibliographical references.eng
dc.format.extentxiii, 110 pages : illustrations (color)eng
dc.identifier.urihttps://hdl.handle.net/10355/93230
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.titleStructural modeling of the 3D genome using machine learningeng
dc.typeThesiseng
thesis.degree.disciplineComputer science (MU)eng
thesis.degree.levelDoctoraleng
thesis.degree.namePh. D.eng


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