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Using multitype branching models to analyze bacterial pathogenicity
Uppsala University, Department of Mathematics, Uppsala, Sweden.
Uppsala University, Department of Mathematics, Uppsala, Sweden.
Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Faculty of Arts and Sciences.ORCID iD: 0000-0002-5816-4345
Polish Academy of Sciences, Institute of Medical Biology, Łódź, Poland.
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2020 (English)In: Mathematica Applicanda, ISSN 1730-2668, Vol. 48, no 1, p. 59-86Article in journal (Refereed) Published
Abstract [en]

We apply multitype, continuous time, Markov branching models to study pathogenicity in E. coli, a bacterium belonging to the genus Escherichia. First, we examine briefly, the properties of multitype branching processes and we also survey some fundamental limit theorems regarding the behavior of such models under various conditions. These theorems are then applied to discrete, state dependent models, in order to analyze pathogenicity in a published clinical data set consisting of 251 strains of E. coli. We use well established methods, incorporating maximum likelihood techniques, to estimate speciation rates as well as the rates of transition between different states of the models. From the analysis, we not only derive new results, but we also verify some preexisting notions about virulent behavior in bacterial strains.

Place, publisher, year, edition, pages
Warsaw, Poland: Polskie Towarzystwo Matematyczne , 2020. Vol. 48, no 1, p. 59-86
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:liu:diva-198055DOI: 10.14708/ma.v48i1.6465Scopus ID: 2-s2.0-85096951212OAI: oai:DiVA.org:liu-198055DiVA, id: diva2:1799641
Funder
Swedish Research Council, 2017-04951
Note

This work is licensed under a Creative Commons Attribution 3.0 License.

Available from: 2023-09-22 Created: 2023-09-22 Last updated: 2025-01-13Bibliographically approved

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Bartoszek, Krzysztof

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