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Maximum likelihood estimates of rearrangement distance: implementing a representation-theoretic approach

Citation

Terauds, V and Sumner, J, Maximum likelihood estimates of rearrangement distance: implementing a representation-theoretic approach, Bulletin of Mathematical Biology, 81, (2) pp. 535-567. ISSN 0092-8240 (2018) [Refereed Article]

Copyright Statement

Copyright Society for Mathematical Biology 2018

DOI: doi:10.1007/s11538-018-0511-6

Abstract

The calculation of evolutionary distance via models of genome rearrangement has an inherent combinatorial complexity. Various algorithms and estimators have been used to address this; however, many of these set quite specific conditions for the underlying model. A recently proposed technique, applying representation theory to calculate evolutionary distance between circular genomes as a maximum likelihood estimate, reduces the computational load by converting the combinatorial problem into a numerical one. We show that the technique may be applied to models with any choice of rearrangements and relative probabilities thereof; we then investigate the symmetry of circular genome rearrangement models in general. We discuss the practical implementation of the technique and, without introducing any bona fide numerical approximations, give the results of some initial calculations for genomes with up to 11 regions.

Item Details

Item Type:Refereed Article
Keywords:rearrangement models, circular genomes, maximum likelihood, evolutionary distance, group representations
Research Division:Mathematical Sciences
Research Group:Applied mathematics
Research Field:Biological mathematics
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in the biological sciences
UTAS Author:Terauds, V (Dr Venta Terauds)
UTAS Author:Sumner, J (Dr Jeremy Sumner)
ID Code:128644
Year Published:2018
Funding Support:Australian Research Council (DE130100423)
Web of Science® Times Cited:9
Deposited By:Mathematics and Physics
Deposited On:2018-10-04
Last Modified:2019-03-07
Downloads:0

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