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An Open-Source Community Resource for Creating, Collecting, Sharing and Applying Predictive Microbial Models (PMM-Lab)

  • Armin A. Weiser
  • Matthias Filter
  • Alexander Falenski
  • Jörgen Brandt
  • Annemarie Käsbohrer
  • Bernd Appel
Part of the Communications in Computer and Information Science book series (CCIS, volume 318)

Introduction

Quantitative microbiological risk assessments (QMRA) in the farm-to-fork continuum heavily rely on mathematical models for growth, survival and inactivation of micro-organisms in different food matrices and processing conditions, collectively subsumed under the heading “predictive microbial models” (PMM). Unfortunately, the currently publicly available PMM are characterized by a great heterogeneity with respect to applicability, quality, validity, documentation, application limits and software requirements.

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References

  1. 1.
    Michael, R.B., Nicolas, C., Fabian, D., Giuseppe, D.F., Thomas, R.G., Florian, G., Thorsten, M., Peter, O., Christoph, S., Bernd, W.: Knime: The Konstanz Information Miner (2006), http://www.knime.org
  2. 2.
    R Development Core Team. R: A language and environment for statistical computing (2008), http://www.r-project.org
  3. 3.
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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Armin A. Weiser
    • 1
  • Matthias Filter
    • 1
  • Alexander Falenski
    • 1
  • Jörgen Brandt
    • 1
  • Annemarie Käsbohrer
    • 1
  • Bernd Appel
    • 1
  1. 1.Dep. Biological SafetyFederal Institute for Risk AssessmentGermany

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