Search: onr:"swepub:oai:DiVA.org:liu-145810" > Predicting pathogen...
Fältnamn | Indikatorer | Metadata |
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000 | 03840naa a2200493 4500 | |
001 | oai:DiVA.org:liu-145810 | |
003 | SwePub | |
008 | 180321s2018 | |||||||||||000 ||eng| | |
009 | oai:DiVA.org:uu-341023 | |
024 | 7 | a https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1458102 URI |
024 | 7 | a https://doi.org/10.1371/journal.pcbi.10059312 DOI |
024 | 7 | a https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-3410232 URI |
040 | a (SwePub)liud (SwePub)uu | |
041 | a engb eng | |
042 | 9 SwePub | |
072 | 7 | a ref2 swepub-contenttype |
072 | 7 | a art2 swepub-publicationtype |
100 | 1 | a Bartoszek, Krzysztofu Linköpings universitet,Statistik och maskininlärning,Filosofiska fakulteten,Uppsala Univ, Sweden4 aut0 (Swepub:liu)krzba67 |
245 | 1 0 | a Predicting pathogenicity behavior in Escherichia coli population through a state dependent model and TRS profiling |
264 | c 2018-01-31 | |
264 | 1 | b PUBLIC LIBRARY SCIENCE,c 2018 |
338 | a electronic2 rdacarrier | |
500 | a Funding Agencies|IMB PAS as part of the statutory research; Knut and Alice Wallenberg Foundation | |
520 | a 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. | |
650 | 7 | a NATURVETENSKAPx Data- och informationsvetenskapx Bioinformatik0 (SwePub)102032 hsv//swe |
650 | 7 | a NATURAL SCIENCESx Computer and Information Sciencesx Bioinformatics0 (SwePub)102032 hsv//eng |
650 | 7 | a NATURVETENSKAPx Biologix Bioinformatik och systembiologi0 (SwePub)106102 hsv//swe |
650 | 7 | a NATURAL SCIENCESx Biological Sciencesx Bioinformatics and Systems Biology0 (SwePub)106102 hsv//eng |
650 | 7 | a NATURVETENSKAPx Matematikx Sannolikhetsteori och statistik0 (SwePub)101062 hsv//swe |
650 | 7 | a NATURAL SCIENCESx Mathematicsx Probability Theory and Statistics0 (SwePub)101062 hsv//eng |
700 | 1 | a Majchrzak, Martau Polish Acad Sci, Poland4 aut |
700 | 1 | a Sakowski, Sebastianu Univ Lodz, Poland4 aut |
700 | 1 | a Kubiak-Szeligowska, Anna B.u Polish Acad Sci, Poland4 aut |
700 | 1 | a Kaj, Ingemar,d 1957-u Uppsala universitet,Analys och sannolikhetsteori,Analysis and Probability,Uppsala Univ, Sweden4 aut0 (Swepub:uu)ingekaj |
700 | 1 | a Parniewski, Pawelu Polish Acad Sci, Poland4 aut |
710 | 2 | a Linköpings universitetb Statistik och maskininlärning4 org |
773 | 0 | t PloS Computational Biologyd : PUBLIC LIBRARY SCIENCEg 14:1q 14:1x 1553-734Xx 1553-7358 |
856 | 4 | u https://liu.diva-portal.org/smash/get/diva2:1192180/FULLTEXT01.pdfx primaryx Raw objecty fulltext:print |
856 | 4 | u https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1005931&type=printable |
856 | 4 | u https://doi.org/10.1371/journal.pcbi.1005931y Fulltext |
856 | 4 | u https://uu.diva-portal.org/smash/get/diva2:1180606/FULLTEXT01.pdfx primaryx Raw objecty fulltext:print |
856 | 4 8 | u https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-145810 |
856 | 4 8 | u https://doi.org/10.1371/journal.pcbi.1005931 |
856 | 4 8 | u https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-341023 |
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