C. D. Bayliss
Mutation and Selection in Bacteria: Modelling and Calibration
Bayliss, C. D.; Fallaize, C.; Howitt, R.; Tretyakov, M. V.
Authors
CHRISTOPHER FALLAIZE Chris.Fallaize@nottingham.ac.uk
Lecturer
R. Howitt
MIKHAIL TRETYAKOV Michael.Tretyakov@nottingham.ac.uk
Professor of Mathematics
Abstract
© 2018, The Author(s). Temporal evolution of a clonal bacterial population is modelled taking into account reversible mutation and selection mechanisms. For the mutation model, an efficient algorithm is proposed to verify whether experimental data can be explained by this model. The selection–mutation model has unobservable fitness parameters, and, to estimate them, we use an Approximate Bayesian Computation algorithm. The algorithms are illustrated using in vitro data for phase variable genes of Campylobacter jejuni.
Citation
Bayliss, C. D., Fallaize, C., Howitt, R., & Tretyakov, M. V. (2019). Mutation and Selection in Bacteria: Modelling and Calibration. Bulletin of Mathematical Biology, 81(3), 639-675. https://doi.org/10.1007/s11538-018-0529-9
Journal Article Type | Article |
---|---|
Acceptance Date | Oct 26, 2018 |
Online Publication Date | Nov 14, 2018 |
Publication Date | Mar 15, 2019 |
Deposit Date | Oct 29, 2018 |
Publicly Available Date | Nov 27, 2018 |
Journal | Bulletin of Mathematical Biology |
Print ISSN | 0092-8240 |
Electronic ISSN | 1522-9602 |
Publisher | Springer Verlag |
Peer Reviewed | Peer Reviewed |
Volume | 81 |
Issue | 3 |
Pages | 639-675 |
DOI | https://doi.org/10.1007/s11538-018-0529-9 |
Keywords | Stochastic modelling, population genetics, phase variable genes,; approximate Bayesian computation; AMS classification 92D25, 62F15, 60J10 |
Public URL | https://nottingham-repository.worktribe.com/output/1203625 |
Publisher URL | https://link.springer.com/article/10.1007%2Fs11538-018-0529-9 |
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Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
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