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Predicting pathogenicity behavior in Escherichia coli population through a state dependent model and TRS profiling
Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Faculty of Arts and Sciences. Uppsala Univ, Sweden.ORCID iD: 0000-0002-5816-4345
Polish Acad Sci, Poland.
Univ Lodz, Poland.
Polish Acad Sci, Poland.
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2018 (English)In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 14, no 1, article id e1005931Article in journal (Refereed) Published
Abstract [en]

The Binary State Speciation and Extinction (BiSSE) model is a branching process based model that allows the diversification rates to be controlled by a binary trait. We develop a general approach, based on the BiSSE model, for predicting pathogenicity in bacterial populations from microsatellites profiling data. A comprehensive approach for predicting pathogenicity in E. coli populations is proposed using the state-dependent branching process model combined with microsatellites TRS-PCR profiling. Additionally, we have evaluated the possibility of using the BiSSE model for estimating parameters from genetic data. We analyzed a real dataset (from 251 E. coli strains) and confirmed previous biological observations demonstrating a prevalence of some virulence traits in specific bacterial sub-groups. The method may be used to predict pathogenicity of other bacterial taxa.

Place, publisher, year, edition, pages
PUBLIC LIBRARY SCIENCE , 2018. Vol. 14, no 1, article id e1005931
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:liu:diva-145810DOI: 10.1371/journal.pcbi.1005931ISI: 000423845000028PubMedID: 29385125OAI: oai:DiVA.org:liu-145810DiVA, id: diva2:1192180
Note

Funding Agencies|IMB PAS as part of the statutory research; Knut and Alice Wallenberg Foundation

Available from: 2018-03-21 Created: 2018-03-21 Last updated: 2019-09-04

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CiteExportLink to record
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