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Spectral analysis of neutral evolution
It has been argued that much of evolution takes place in the absence of fitness gradients. Such periods of evolution can be analysed by examining the mutational network formed by sequences of equal fitness, that is, the neutral network. It has been demonstrated that, in large populations under a hig...
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| Format: | Thesis |
| Language: | English |
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Department of Computer Science
2018
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| _version_ | 1867613155234938880 |
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| access_status_str | Open Access |
| author | Shorten, David |
| author2 | Nitschke, Geoff Stuart |
| author_browse | Nitschke, Geoff Stuart Shorten, David |
| author_facet | Nitschke, Geoff Stuart Shorten, David |
| author_sort | Shorten, David |
| collection | Thesis |
| description | It has been argued that much of evolution takes place in the absence of fitness gradients. Such periods of evolution can be analysed by examining the mutational network formed by sequences of equal fitness, that is, the neutral network. It has been demonstrated that, in large populations under a high mutation rate, the population distribution over the neutral network and average mutational robustness are given by the principal eigenvector and eigen- value, respectively, of the network's adjacency matrix. However, little progress has been made towards understanding the manner in which the topology of the neutral network influences the resulting population distribution and robustness. In this work, we build on recent results from spectral graph theory and utilize numerical methods to enhance our understanding of how populations distribute themselves over neutral networks. We demonstrate that, in the presence of certain topological features, the population will undergo an exploration catastrophe and become confined to a small portion of the network. We further derive approximations, in terms of mutational biases, for the population distribution and average robustness in networks with a homogeneous structure. The applicability of these results is explored, first, by a detailed review of the literature in both evolutionary computing and biology concerning the structure of neutral networks. This is extended by studying the actual and predicted population distribution over the neutral networks of H1N1 and H3N2 influenza haemagglutinin during seasons between 2005 and 2016. It is shown that, in some instances, these populations experience an exploration catastrophe. These results provide insight into the behaviour of populations on neutral networks, demonstrating that neutrality does not necessarily lead to an exploration of genotype/phenotype space or an associated increase in population diversity. Moreover, they provide a plausible explanation for conflicting results concerning the relationship between robustness and evolvability. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/27420 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:31:38.662Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| publisher | Department of Computer Science |
| publisherStr | Department of Computer Science |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/27420 Spectral analysis of neutral evolution Shorten, David Nitschke, Geoff Stuart Eiben, Agoston Evolutionary Computing Neutral Networks It has been argued that much of evolution takes place in the absence of fitness gradients. Such periods of evolution can be analysed by examining the mutational network formed by sequences of equal fitness, that is, the neutral network. It has been demonstrated that, in large populations under a high mutation rate, the population distribution over the neutral network and average mutational robustness are given by the principal eigenvector and eigen- value, respectively, of the network's adjacency matrix. However, little progress has been made towards understanding the manner in which the topology of the neutral network influences the resulting population distribution and robustness. In this work, we build on recent results from spectral graph theory and utilize numerical methods to enhance our understanding of how populations distribute themselves over neutral networks. We demonstrate that, in the presence of certain topological features, the population will undergo an exploration catastrophe and become confined to a small portion of the network. We further derive approximations, in terms of mutational biases, for the population distribution and average robustness in networks with a homogeneous structure. The applicability of these results is explored, first, by a detailed review of the literature in both evolutionary computing and biology concerning the structure of neutral networks. This is extended by studying the actual and predicted population distribution over the neutral networks of H1N1 and H3N2 influenza haemagglutinin during seasons between 2005 and 2016. It is shown that, in some instances, these populations experience an exploration catastrophe. These results provide insight into the behaviour of populations on neutral networks, demonstrating that neutrality does not necessarily lead to an exploration of genotype/phenotype space or an associated increase in population diversity. Moreover, they provide a plausible explanation for conflicting results concerning the relationship between robustness and evolvability. 2018-02-07T12:18:22Z 2018-02-07T12:18:22Z 2017 Master Thesis Masters MSc http://hdl.handle.net/11427/27420 eng application/pdf Department of Computer Science Faculty of Science University of Cape Town |
| spellingShingle | Evolutionary Computing Neutral Networks Shorten, David Spectral analysis of neutral evolution |
| thesis_degree_str | Master's |
| title | Spectral analysis of neutral evolution |
| title_full | Spectral analysis of neutral evolution |
| title_fullStr | Spectral analysis of neutral evolution |
| title_full_unstemmed | Spectral analysis of neutral evolution |
| title_short | Spectral analysis of neutral evolution |
| title_sort | spectral analysis of neutral evolution |
| topic | Evolutionary Computing Neutral Networks |
| url | http://hdl.handle.net/11427/27420 |
| work_keys_str_mv | AT shortendavid spectralanalysisofneutralevolution |