In this manuscript, we advocate that biological uncertainties need to be considered foundational facets that must be incorporated in models. This will improve our understanding and identification of microbial traits and provide fundamental insights on microbial systems.
Significance and Impact
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.
- We employ a statistical model-checking (SMC) method that combines model checking with sensitivity analyses.
- We then embed the uncertainty of the parameter values into the models by assigning each parameter to a probability distribution based on its potential values informed by lab or field experiments
Delahaye B, Eveillard D, Bouskill NJ (2018). On the Power of Uncertainties in Microbial System Modeling: No Need To Hide Them Anymore. M-Systems. 2 (6) DOI: 10.1128/mSystems.00169-17.