Mathematical stochastic models for DNA

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dc.contributor.advisorNandori, Peter
dc.contributor.authorMoise, Yonah
dc.date.accessioned2023-06-05T15:01:45Z
dc.date.available2023-06-05T15:01:45Z
dc.date.issued2023-05
dc.descriptionUndergraduate honors thesis / Open Accessen_US
dc.description.abstractKimura’s neutral theory of molecular evolution gave rise to several models by which to study genetic data. Such models include the infinite alleles model and the infinite sites model. We studied these models, and present them here in an clear and algorithmic style. We coded these models in Python, using Monte Carlo methods to calculate probabilities and perform tests of hypothesis against real-world data.en_US
dc.description.sponsorshipFunded in part by the Jay and Jeanie Schottenstein Honors programen_US
dc.identifier.citationMoise, Y. (2023, May). Mathematical stochastic models for DNA [undergraduate honors thesis, Yeshiva University].en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12202/8951
dc.language.isoen_USen_US
dc.publisherYeshiva Universityen_US
dc.relation.ispartofseriesJay and Jeanie Schottenstein Honors Program;May 2023
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectmolecular evolutionen_US
dc.subjectgenetic dataen_US
dc.subjectalgorithmic styleen_US
dc.subjectPythonen_US
dc.subjectMonte Carloen_US
dc.subjectprobabilitiesen_US
dc.titleMathematical stochastic models for DNAen_US
dc.typeThesisen_US

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