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A symmetry-inclusive algebraic approach to genome rearrangement

journal contribution
posted on 2023-05-21, 06:47 authored by Venta TeraudsVenta Terauds, Joshua StevensonJoshua Stevenson, Jeremy SumnerJeremy Sumner
Of the many modern approaches to calculating evolutionary distance via models of genome rearrangement, most are tied to a particular set of genomic modelling assumptions and to a restricted class of allowed rearrangements. The "position paradigm", in which genomes are represented as permutations signifying the position (and orientation) of each region, enables a refined model-based approach, where one can select biologically plausible rearrangements and assign to them relative probabilities/costs. Here, one must further incorporate any underlying structural symmetry of the genomes into the calculations and ensure that this symmetry is reflected in the model. In our recently-introduced framework of {\em genome algebras}, each genome corresponds to an element that simultaneously incorporates all of its inherent physical symmetries. The representation theory of these algebras then provides a natural model of evolution via rearrangement as a Markov chain. Whilst the implementation of this framework to calculate distances for genomes with `practical' numbers of regions is currently computationally infeasible, we consider it to be a significant theoretical advance: one can incorporate different genomic modelling assumptions, calculate various genomic distances, and compare the results under different rearrangement models. The aim of this paper is to demonstrate some of these features.

History

Publication title

Journal of Bioinformatics and Computational Biology

Volume

19

Issue

6

Article number

2140015

Number

2140015

ISSN

0219-7200

Department/School

School of Natural Sciences

Publisher

World Scientific Publishing Europe Ltd.

Place of publication

United Kingdom

Rights statement

Copyright 2021 World Scientific Publishing Europe Ltd.

Repository Status

  • Restricted

Socio-economic Objectives

Expanding knowledge in the biological sciences; Expanding knowledge in the mathematical sciences

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