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dc.contributor.authorJackson, Benjamin D.
dc.contributor.authorConnolly, James M.
dc.contributor.authorGerlach, Robin
dc.contributor.authorKlapper, Issac
dc.contributor.authorParker, Albert E.
dc.identifier.citationJackson, Benjamin D., Connolly, James M., Gerlach, Robin, Klapper, Isaac, & Parker, Albert E. (2021). Bayesian estimation and uncertainty quantification in models of urea hydrolysis by E. coli biofilms. Inverse Problems in Science and Engineering, 1–24.
dc.description.abstractUrea-hydrolysing biofilms are crucial to applications in medicine, engineering, and science. Quantitative information about ureolysis rates in biofilms is required to model these applications. We formulate a novel model of urea consumption in a biofilm that allows different kinetics, for example either first order or Michaelis-Menten. The model is fit it to synthetic data to validate and compare two approaches: Bayesian and nonlinear least squares (NLS), commonly used by biofilm practitioners. The shortcomings of NLS motivate the Bayesian approach where a simple Markov Chain Monte Carlo (MCMC) sampler is applied. The model is then fit to real data of influent and effluent urea concentrations from experiments on biofilms of Escherichia coli. Results from synthetic data aid in interpreting results from real data, where first order and Michaelis-Menten kinetic models are compared. The method shows potential for general applications requiring biofilm kinetic information.en_US
dc.publisherInforma UK Limiteden_US
dc.titleBayesian estimation and uncertainty quantification in models of urea hydrolysis by E. coli biofilmsen_US
mus.citation.journaltitleInverse Problems in Science and Engineeringen_US
mus.relation.collegeCollege of Engineeringen_US
mus.relation.collegeCollege of Letters & Scienceen_US
mus.relation.departmentMathematical Sciences.en_US
mus.relation.universityMontana State University - Bozemanen_US
mus.relation.researchgroupCenter for Biofilm Engineering.en_US

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