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dc.contributor.advisorSætrom, Pålnb_NO
dc.contributor.advisorDrabløs, Finnnb_NO
dc.contributor.advisorMartinek, Tomasnb_NO
dc.contributor.authorVisnovsky, Mareknb_NO
dc.date.accessioned2014-12-19T13:40:40Z
dc.date.available2014-12-19T13:40:40Z
dc.date.created2013-10-24nb_NO
dc.date.issued2013nb_NO
dc.identifier659286nb_NO
dc.identifierntnudaim:9926nb_NO
dc.identifier.urihttp://hdl.handle.net/11250/253496
dc.description.abstractThe novel method for a prediction of nucleosome positions in yeast, based on Hidden Markov models extended by duration state modeling, was developed, implemented and tested, using data from Brogaard et al. (Brogaard K, Wang J-P, Widom, J. Nature 486(7404), 496-501 (2012). doi:10.1038/nature11142) for training and testing. Furthermore, several experiments were conducted to derive an importance of various features of nucleosome sequence preferences and global organization.nb_NO
dc.languageengnb_NO
dc.publisherInstitutt for datateknikk og informasjonsvitenskapnb_NO
dc.titlePrediction and analysis of nucleosome positions in yeastnb_NO
dc.typeMaster thesisnb_NO
dc.source.pagenumber61nb_NO
dc.contributor.departmentNorges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for datateknikk og informasjonsvitenskapnb_NO


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