On the Power of Uncertainties in Microbial System Modeling: No Need To Hide Them Anymore
- Centre National de la Recherche Scientifique (CNRS), Nantes (France)
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
For decades, microbiologists have considered uncertainties as an undesired side effect of experimental protocols. As a consequence, standard microbial system modeling strives to hide uncertainties for the sake of deterministic understanding. However, recent studies have highlighted greater experimental variability than expected and emphasized uncertainties not as a weakness but as a necessary feature of complex microbial systems. We therefore advocate that biological uncertainties need to be considered foundational facets that must be incorporated in models. Not only will understanding these uncertainties improve our understanding and identification of microbial traits, it will also provide fundamental insights on microbial systems as a whole. Taking into account uncertainties within microbial models calls for new validation techniques. Formal verification already overcomes this shortcoming by proposing modeling frameworks and validation techniques dedicated to probabilistic models. However, further work remains to extract the full potential of such techniques in the context of microbial models. Herein, we demonstrate how statistical model checking can enhance the development of microbial models by building confidence in the estimation of critical parameters and through improved sensitivity analyses.
- Research Organization:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Biological and Environmental Research (BER); Centre National de la Recherche Scientifique (CNRS)
- Grant/Contract Number:
- AC02-05CH11231
- OSTI ID:
- 1476559
- Journal Information:
- mSystems, Vol. 2, Issue 6; ISSN 2379-5077
- Publisher:
- American Society for MicrobiologyCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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journal | January 2020 |
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