First step in using molecular data for microbial food safety risk assessment; hazard identification of Escherichia coli O157:H7 by coupling genomic data with in vitro adherence to human epithelial cells-Reference-Cited by-同舟云学术

First step in using molecular data for microbial food safety risk assessment; hazard identification of Escherichia coli O157:H7 by coupling genomic data with in vitro adherence to human epithelial cells

Published:2015-11 Issue: Volume:213 Page:130-138
ISSN:0168-1605
Container-title:International Journal of Food Microbiology
language:en
Short-container-title:International Journal of Food Microbiology

Author:

Pielaat Annemarie,Boer Martin P.,Wijnands Lucas M.,van Hoek Angela H.A.M.,Bouw El,Barker Gary C.,Teunis Peter F.M.,Aarts Henk J.M.,Franz Eelco

Funder

RIVM

Biotechnology and Biological Sciences Research Council

Publisher

Elsevier BV

Subject

General Medicine,Microbiology,Food Science

Reference55 articles.

1. Impact of genomics on microbial food safety;Abee;Trends Biotechnol.,2004

2. Increased adherence and expression of virulence genes in a lineage of Escherichia coli O157:H7 commonly associated with human infections;Abu-Ali;PLoS ONE,2010

3. Modeling gene associations for virulence classification of verocytotoxin-producing E. coli (VTEC) from patients and beef;Andersson;Virulence,2011

4. Gene expression induced in Escherichia coli O157:H7 upon exposure to model apple juice;Bergholz;Appl. Environ. Microbiol.,2009

5. In Vitro and In Vivo Virulence of Salmonella Typhimurium DT104: A Parallelogram Approach;Berk,2008

Cited by 36 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Advancements in Predictive Microbiology: Integrating New Technologies for Efficient Food Safety Models;International Journal of Microbiology;2024-05-17

2. Improvement of quantitative microbiological risk assessment (QMRA) methodology through integration with gaenetic data;EFSA Journal;2023-11

3. Molecular detection and characterization of foodborne bacteria: Recent progresses and remaining challenges;Comprehensive Reviews in Food Science and Food Safety;2023-04-11

4. Machine learning to predict foodborne salmonellosis outbreaks based on genome characteristics and meteorological trends;Current Research in Food Science;2023

5. Role of real-time DNA analyses, biomarkers, resistance measurement, and ecosystem management in Campylobacter risk analysis;Present Knowledge in Food Safety;2023