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Natural selection inference and sampling formulae
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Khromov, Pavel. Natural selection inference and sampling formulae. Retrieved from https://doi.org/doi:10.7282/t3-c581-th34

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TitleNatural selection inference and sampling formulae
NameKhromov, Pavel (author); Morozov, Alexandre V (chair); Sengupta, Anirvan (internal member); Chandra, Premala (internal member); Diaconescu, Duiliu E (internal member); Ellison, Christopher (outside member); Rutgers University; School of Graduate Studies
Date Created2020
Other Date2020-05 (degree)
SubjectFitness landscapes, Physics and Astronomy
Extent1 online resource (x, 88 pages) : illustrations
DescriptionTheory of evolution provides a simple, flexible, and elegant framework to study and explain life around us. Population genetics is a mathematical wing of evolutionary theory. One of its key results connects steady state distribution of observable traits in a population with evolutionary parameters like mutation rate and fitness landscape in which the population is evolving. If number of trait types is very large, which is a relevant limit for molecular biology, then Ewens sampling formula provides a description of the steady state for the case with no natural selection acting on the population. We provide a generalization of this formula to arbitrary fitness landscape and use it to infer distribution of mutation rate and selection pressure along fruit fly chromosomes from sequenced data.
NotePh.D.
NoteIncludes bibliographical references
Genretheses, ETD doctoral
Persistent URLhttps://doi.org/doi:10.7282/t3-c581-th34
LanguageEnglish
CollectionSchool of Graduate Studies Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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