A new algebraic approach to genome rearrangement models.


Journal

Journal of mathematical biology
ISSN: 1432-1416
Titre abrégé: J Math Biol
Pays: Germany
ID NLM: 7502105

Informations de publication

Date de publication:
05 05 2022
Historique:
received: 21 12 2020
accepted: 31 03 2022
revised: 24 01 2022
entrez: 4 5 2022
pubmed: 5 5 2022
medline: 7 5 2022
Statut: epublish

Résumé

We present a unified framework for modelling genomes and their rearrangements in a genome algebra, as elements that simultaneously incorporate all physical symmetries. Building on previous work utilising the group algebra of the symmetric group, we explicitly construct the genome algebra for the case of unsigned circular genomes with dihedral symmetry and show that the maximum likelihood estimate (MLE) of genome rearrangement distance can be validly and more efficiently performed in this setting. We then construct the genome algebra for a more general case, that is, for genomes that may be represented by elements of an arbitrary group and symmetry group, and show that the MLE computations can be performed entirely within this framework. There is no prescribed model in this framework; that is, it allows any choice of rearrangements that preserve the set of regions, along with arbitrary weights. Further, since the likelihood function is built from path probabilities-a generalisation of path counts-the framework may be utilised for any distance measure that is based on path probabilities.

Identifiants

pubmed: 35508785
doi: 10.1007/s00285-022-01744-0
pii: 10.1007/s00285-022-01744-0
pmc: PMC9068684
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

49

Informations de copyright

© 2022. The Author(s).

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Auteurs

Venta Terauds (V)

Discipline of Mathematics, School of Natural Sciences, University of Tasmania, Private Bag 37, Sandy Bay, TAS, 7001, Australia. venta.terauds@utas.edu.au.

Jeremy Sumner (J)

Discipline of Mathematics, School of Natural Sciences, University of Tasmania, Private Bag 37, Sandy Bay, TAS, 7001, Australia.

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Classifications MeSH