The model-specific Markov embedding problem for symmetric group-based models.

Embedding problem Evolutionary models Group-based models Markov generator Markov matrix

Journal

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

Informations de publication

Date de publication:
09 09 2021
Historique:
received: 15 06 2020
accepted: 17 08 2021
revised: 04 08 2021
entrez: 9 9 2021
pubmed: 10 9 2021
medline: 21 10 2021
Statut: epublish

Résumé

We study model embeddability, which is a variation of the famous embedding problem in probability theory, when apart from the requirement that the Markov matrix is the matrix exponential of a rate matrix, we additionally ask that the rate matrix follows the model structure. We provide a characterisation of model embeddable Markov matrices corresponding to symmetric group-based phylogenetic models. In particular, we provide necessary and sufficient conditions in terms of the eigenvalues of symmetric group-based matrices. To showcase our main result on model embeddability, we provide an application to hachimoji models, which are eight-state models for synthetic DNA. Moreover, our main result on model embeddability enables us to compute the volume of the set of model embeddable Markov matrices relative to the volume of other relevant sets of Markov matrices within the model.

Identifiants

pubmed: 34499233
doi: 10.1007/s00285-021-01656-5
pii: 10.1007/s00285-021-01656-5
pmc: PMC8429190
doi:

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

33

Informations de copyright

© 2021. The Author(s).

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Auteurs

Muhammad Ardiyansyah (M)

Department of Mathematics and Systems Analysis, Aalto University, Espoo, Finland.

Dimitra Kosta (D)

School of Mathematics, University of Edinburgh, Edinburgh, UK.

Kaie Kubjas (K)

Department of Mathematics and Systems Analysis, Aalto University, Espoo, Finland. kaie.kubjas@aalto.fi.

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Classifications MeSH