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    A Syst-OMICS Approach to Ensuring Food Safety and Reducing the Economic Burden of Salmonellosis.

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    Authors
    Emond-Rheault, Jean-Guillaume
    Jeukens, Julie
    Freschi, Luca
    Kukavica-Ibrulj, Irena
    Boyle, Brian
    Dupont, Marie-Josée
    Colavecchio, Anna
    Barrere, Virginie
    Cadieux, Brigitte
    Arya, Gitanjali
    Bekal, Sadjia
    Berry, Chrystal
    Burnett, Elton
    Cavestri, Camille
    Chapin, Travis K
    Crouse, Alanna
    Daigle, France
    Danyluk, Michelle D
    Delaquis, Pascal
    Dewar, Ken
    Doualla-Bell, Florence
    Fliss, Ismail
    Fong, Karen
    Fournier, Eric
    Franz, Eelco
    Garduno, Rafael
    Gill, Alexander
    Gruenheid, Samantha
    Harris, Linda
    Huang, Carol B
    Huang, Hongsheng
    Johnson, Roger
    Joly, Yann
    Kerhoas, Maud
    Kong, Nguyet
    Lapointe, Gisèle
    Larivière, Line
    Loignon, Stéphanie
    Malo, Danielle
    Moineau, Sylvain
    Mottawea, Walid
    Mukhopadhyay, Kakali
    Nadon, Céline
    Nash, John
    Ngueng Feze, Ida
    Ogunremi, Dele
    Perets, Ann
    Pilar, Ana V
    Reimer, Aleisha R
    Robertson, James
    Rohde, John
    Sanderson, Kenneth E
    Song, Lingqiao
    Stephan, Roger
    Tamber, Sandeep
    Thomassin, Paul
    Tremblay, Denise
    Usongo, Valentine
    Vincent, Caroline
    Wang, Siyun
    Weadge, Joel T
    Wiedmann, Martin
    Wijnands, Lucas
    Wilson, Emily D
    Wittum, Thomas
    Yoshida, Catherine
    Youfsi, Khadija
    Zhu, Lei
    Weimer, Bart C
    Goodridge, Lawrence
    Levesque, Roger C
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    Type
    Article
    Language
    en
    
    Metadata
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    Title
    A Syst-OMICS Approach to Ensuring Food Safety and Reducing the Economic Burden of Salmonellosis.
    Published in
    Front Microbiol 2017, 8:996
    Publiekssamenvatting
    The Salmonella Syst-OMICS consortium is sequencing 4,500 Salmonella genomes and building an analysis pipeline for the study of Salmonella genome evolution, antibiotic resistance and virulence genes. Metadata, including phenotypic as well as genomic data, for isolates of the collection are provided through the Salmonella Foodborne Syst-OMICS database (SalFoS), at https://salfos.ibis.ulaval.ca/. Here, we present our strategy and the analysis of the first 3,377 genomes. Our data will be used to draw potential links between strains found in fresh produce, humans, animals and the environment. The ultimate goals are to understand how Salmonella evolves over time, improve the accuracy of diagnostic methods, develop control methods in the field, and identify prognostic markers for evidence-based decisions in epidemiology and surveillance.
    DOI
    10.3389/fmicb.2017.00996
    PMID
    28626454
    URI
    http://hdl.handle.net/10029/620969
    ae974a485f413a2113503eed53cd6c53
    10.3389/fmicb.2017.00996
    Scopus Count
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