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Improved models of biological sequence evolution

Thesis (PhD)--Stellenbosch University, 2012.

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Main Author: Murrel, Benjamin
Other Authors: Scheffler, Konrad
Format: Thesis
Language:en_ZA
Published: Stellenbosch : Stellenbosch University 2012
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access_status_str Open Access
author Murrel, Benjamin
author2 Scheffler, Konrad
author_browse Murrel, Benjamin
Scheffler, Konrad
author_facet Scheffler, Konrad
Murrel, Benjamin
author_sort Murrel, Benjamin
collection Thesis
dc_rights_str_mv Stellenbosch University
description Thesis (PhD)--Stellenbosch University, 2012.
format Thesis
id oai:scholar.sun.ac.za:10019.1/71870
institution Stellenbosch University (South Africa)
language en_ZA
last_indexed 2026-06-10T12:46:37.536Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository
publishDate 2012
publishDateRange 2012
publishDateSort 2012
publisher Stellenbosch : Stellenbosch University
publisherStr Stellenbosch : Stellenbosch University
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source_str SUNScholar — Stellenbosch University Repository
spelling oai:scholar.sun.ac.za:10019.1/71870 Improved models of biological sequence evolution Murrel, Benjamin Scheffler, Konrad Stellenbosch University. Faculty of Science. Dept. of Mathematical Sciences. Molecular evolution Phylogenetic models -- Mathematical models Natural selection Markov processes Molecular evolution -- Data processing Dissertations -- Mathematical sciences Theses -- Mathematical sciences Dissertations -- Computer science Theses -- Computer science Thesis (PhD)--Stellenbosch University, 2012. ENGLISH ABSTRACT: Computational molecular evolution is a field that attempts to characterize how genetic sequences evolve over phylogenetic trees – the branching processes that describe the patterns of genetic inheritance in living organisms. It has a long history of developing progressively more sophisticated stochastic models of evolution. Through a probabilist’s lens, this can be seen as a search for more appropriate ways to parameterize discrete state continuous time Markov chains to better encode biological reality, matching the historical processes that created empirical data sets, and creating useful tools that allow biologists to test specific hypotheses about the evolution of the organisms or the genes that interest them. This dissertation is an attempt to fill some of the gaps that persist in the literature, solving what we see as existing open problems. The overarching theme of this work is how to better model variation in the action of natural selection at multiple levels: across genes, between sites, and over time. Through four published journal articles and a fifth in preparation, we present amino acid and codon models that improve upon existing approaches, providing better descriptions of the process of natural selection and better tools to detect adaptive evolution. AFRIKAANSE OPSOMMING: Komputasionele molekulêre evolusie is ’n navorsingsarea wat poog om die evolusie van genetiese sekwensies oor filogenetiese bome – die vertakkende prosesse wat die patrone van genetiese oorerwing in lewende organismes beskryf – te karakteriseer. Dit het ’n lang geskiedenis waartydens al hoe meer gesofistikeerde waarskynlikheidsmodelle van evolusie ontwikkel is. Deur die lens van waarskynlikheidsleer kan hierdie proses gesien word as ’n soektog na meer gepasde metodes om diskrete-toestand kontinuë-tyd Markov kettings te parametriseer ten einde biologiese realiteit beter te enkodeer – op so ’n manier dat die historiese prosesse wat tot die vorming van biologiese sekwensies gelei het nageboots word, en dat nuttige metodes geskep word wat bioloë toelaat om spesifieke hipotesisse met betrekking tot die evolusie van belanghebbende organismes of gene te toets. Hierdie proefskrif is ’n poging om sommige van die gapings wat in die literatuur bestaan in te vul en bestaande oop probleme op te los. Die oorkoepelende tema is verbeterde modellering van variasie in die werking van natuurlike seleksie op verskeie vlakke: variasie van geen tot geen, variasie tussen posisies in gene en variasie oor tyd. Deur middel van vier gepubliseerde joernaalartikels en ’n vyfde artikel in voorbereiding, bied ons aminosuur- en kodon-modelle aan wat verbeter op bestaande benaderings – hierdie modelle verskaf beter beskrywings van die proses van natuurlike seleksie sowel as beter metodes om gevalle van aanpassing in evolusie te vind. Doctoral 2012-10-11T05:36:23Z 2012-12-12T08:15:45Z 2012-10-11T05:36:23Z 2012-12-12T08:15:45Z 2012-12 Thesis http://hdl.handle.net/10019.1/71870 en_ZA Stellenbosch University 1 v. (various pagings) application/pdf Stellenbosch : Stellenbosch University
spellingShingle Molecular evolution
Phylogenetic models -- Mathematical models
Natural selection
Markov processes
Molecular evolution -- Data processing
Dissertations -- Mathematical sciences
Theses -- Mathematical sciences
Dissertations -- Computer science
Theses -- Computer science
Murrel, Benjamin
Improved models of biological sequence evolution
title Improved models of biological sequence evolution
title_full Improved models of biological sequence evolution
title_fullStr Improved models of biological sequence evolution
title_full_unstemmed Improved models of biological sequence evolution
title_short Improved models of biological sequence evolution
title_sort improved models of biological sequence evolution
topic Molecular evolution
Phylogenetic models -- Mathematical models
Natural selection
Markov processes
Molecular evolution -- Data processing
Dissertations -- Mathematical sciences
Theses -- Mathematical sciences
Dissertations -- Computer science
Theses -- Computer science
url http://hdl.handle.net/10019.1/71870
work_keys_str_mv AT murrelbenjamin improvedmodelsofbiologicalsequenceevolution