A topic model based approach to inferring episodic directional selection in protein coding sequences

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dc.contributor.advisorLacerda, Miguelen_ZA
dc.contributor.authorSadiq, Hassan Taiwoen_ZA
dc.date.accessioned2016-06-10T10:53:55Z
dc.date.available2016-06-10T10:53:55Z
dc.date.issued2015en_ZA
dc.description.abstractPathogens, such as HIV and influenza, evolve in response to the selective pressures of their host environments accumulating changes in their genomes that offer fitness benefits. This selective pressure is characterised by three properties: (1.) it is episodic, tracking changes in the adaptive immune response and drug therapy, (2.) it is directional in that only particular amino acid substitutions are favoured and (3.) it varies between genomic loci. Most previous models have ignored or inadequately addressed some of these phenomena. This work extends recent approaches to modelling episodic directional selection acting on protein-coding sequences. We use inference techniques within the topic model framework to identify loci evolving under natural selection. A notable example of such techniques are the variational Bayesian methods. We show that our approach performs well in terms of specificity and power, and demonstrate its utility by applying it to some real datasets of HIV sequences.en_ZA
dc.identifier.apacitationSadiq, H. T. (2015). <i>A topic model based approach to inferring episodic directional selection in protein coding sequences</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Statistical Sciences. Retrieved from http://hdl.handle.net/11427/20013en_ZA
dc.identifier.chicagocitationSadiq, Hassan Taiwo. <i>"A topic model based approach to inferring episodic directional selection in protein coding sequences."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Statistical Sciences, 2015. http://hdl.handle.net/11427/20013en_ZA
dc.identifier.citationSadiq, H. 2015. A topic model based approach to inferring episodic directional selection in protein coding sequences. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Sadiq, Hassan Taiwo AB - Pathogens, such as HIV and influenza, evolve in response to the selective pressures of their host environments accumulating changes in their genomes that offer fitness benefits. This selective pressure is characterised by three properties: (1.) it is episodic, tracking changes in the adaptive immune response and drug therapy, (2.) it is directional in that only particular amino acid substitutions are favoured and (3.) it varies between genomic loci. Most previous models have ignored or inadequately addressed some of these phenomena. This work extends recent approaches to modelling episodic directional selection acting on protein-coding sequences. We use inference techniques within the topic model framework to identify loci evolving under natural selection. A notable example of such techniques are the variational Bayesian methods. We show that our approach performs well in terms of specificity and power, and demonstrate its utility by applying it to some real datasets of HIV sequences. DA - 2015 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2015 T1 - A topic model based approach to inferring episodic directional selection in protein coding sequences TI - A topic model based approach to inferring episodic directional selection in protein coding sequences UR - http://hdl.handle.net/11427/20013 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/20013
dc.identifier.vancouvercitationSadiq HT. A topic model based approach to inferring episodic directional selection in protein coding sequences. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Statistical Sciences, 2015 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/20013en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Statistical Sciencesen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherDecision Sciences and Analyticsen_ZA
dc.titleA topic model based approach to inferring episodic directional selection in protein coding sequencesen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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