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A Bayesian approach to modelling the impact of hydrodynamic shear stress on biofilm deformation

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A Bayesian approach to modelling the impact of hydrodynamic shear stress on biofilm deformation. / Oyebamiji, Oluwole Kehinde; Wilkinson, Darren J.; Pahala Gedara, Jayathilake; Rushton, Steve P.; Bridgens, Ben ; Li, Bowen.

In: PLoS ONE, Vol. 13, No. 4, e0195484, 12.04.2018.

Research output: Contribution to journalJournal articlepeer-review

Harvard

Oyebamiji, OK, Wilkinson, DJ, Pahala Gedara, J, Rushton, SP, Bridgens, B & Li, B 2018, 'A Bayesian approach to modelling the impact of hydrodynamic shear stress on biofilm deformation', PLoS ONE, vol. 13, no. 4, e0195484. https://doi.org/10.1371/journal.pone.0195484

APA

Oyebamiji, O. K., Wilkinson, D. J., Pahala Gedara, J., Rushton, S. P., Bridgens, B., & Li, B. (2018). A Bayesian approach to modelling the impact of hydrodynamic shear stress on biofilm deformation. PLoS ONE, 13(4), [e0195484]. https://doi.org/10.1371/journal.pone.0195484

Vancouver

Oyebamiji OK, Wilkinson DJ, Pahala Gedara J, Rushton SP, Bridgens B, Li B. A Bayesian approach to modelling the impact of hydrodynamic shear stress on biofilm deformation. PLoS ONE. 2018 Apr 12;13(4). e0195484. https://doi.org/10.1371/journal.pone.0195484

Author

Oyebamiji, Oluwole Kehinde ; Wilkinson, Darren J. ; Pahala Gedara, Jayathilake ; Rushton, Steve P. ; Bridgens, Ben ; Li, Bowen. / A Bayesian approach to modelling the impact of hydrodynamic shear stress on biofilm deformation. In: PLoS ONE. 2018 ; Vol. 13, No. 4.

Bibtex

@article{7c32fb3248414e2a91bdd6e42de9ddff,
title = "A Bayesian approach to modelling the impact of hydrodynamic shear stress on biofilm deformation",
abstract = "We investigate the feasibility of using a surrogate-based method to emulate the deformation and detachment behaviour of a biofilm in response to hydrodynamic shear stress. The influence of shear force, growth rate and viscoelastic parameters on the patterns of growth, structure and resulting shape of microbial biofilms was examined. We develop a statistical modelling approach to this problem, using combination of Bayesian Poisson regression and dynamic linear models for the emulation. We observe that the hydrodynamic shear force affects biofilm deformation in line with some literature. Sensitivity results also showed that the expected number of shear events, shear flow, yield coefficient for heterotrophic bacteria and extracellular polymeric substance (EPS) stiffness per unit EPS mass are the four principal mechanisms governing the bacteria detachment in this study. The sensitivity of the model parameters is temporally dynamic, emphasising the significance of conducting the sensitivity analysis across multiple time points. The surrogate models are shown to perform well, and produced ≈ 480 fold increase in computational efficiency. We conclude that a surrogate-based approach is effective, and resulting biofilm structure is determined primarily by a balance between bacteria growth, viscoelastic parameters and applied shear stress.",
author = "Oyebamiji, {Oluwole Kehinde} and Wilkinson, {Darren J.} and {Pahala Gedara}, Jayathilake and Rushton, {Steve P.} and Ben Bridgens and Bowen Li",
year = "2018",
month = apr,
day = "12",
doi = "10.1371/journal.pone.0195484",
language = "English",
volume = "13",
journal = "PLoS ONE",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "4",

}

RIS

TY - JOUR

T1 - A Bayesian approach to modelling the impact of hydrodynamic shear stress on biofilm deformation

AU - Oyebamiji, Oluwole Kehinde

AU - Wilkinson, Darren J.

AU - Pahala Gedara, Jayathilake

AU - Rushton, Steve P.

AU - Bridgens, Ben

AU - Li, Bowen

PY - 2018/4/12

Y1 - 2018/4/12

N2 - We investigate the feasibility of using a surrogate-based method to emulate the deformation and detachment behaviour of a biofilm in response to hydrodynamic shear stress. The influence of shear force, growth rate and viscoelastic parameters on the patterns of growth, structure and resulting shape of microbial biofilms was examined. We develop a statistical modelling approach to this problem, using combination of Bayesian Poisson regression and dynamic linear models for the emulation. We observe that the hydrodynamic shear force affects biofilm deformation in line with some literature. Sensitivity results also showed that the expected number of shear events, shear flow, yield coefficient for heterotrophic bacteria and extracellular polymeric substance (EPS) stiffness per unit EPS mass are the four principal mechanisms governing the bacteria detachment in this study. The sensitivity of the model parameters is temporally dynamic, emphasising the significance of conducting the sensitivity analysis across multiple time points. The surrogate models are shown to perform well, and produced ≈ 480 fold increase in computational efficiency. We conclude that a surrogate-based approach is effective, and resulting biofilm structure is determined primarily by a balance between bacteria growth, viscoelastic parameters and applied shear stress.

AB - We investigate the feasibility of using a surrogate-based method to emulate the deformation and detachment behaviour of a biofilm in response to hydrodynamic shear stress. The influence of shear force, growth rate and viscoelastic parameters on the patterns of growth, structure and resulting shape of microbial biofilms was examined. We develop a statistical modelling approach to this problem, using combination of Bayesian Poisson regression and dynamic linear models for the emulation. We observe that the hydrodynamic shear force affects biofilm deformation in line with some literature. Sensitivity results also showed that the expected number of shear events, shear flow, yield coefficient for heterotrophic bacteria and extracellular polymeric substance (EPS) stiffness per unit EPS mass are the four principal mechanisms governing the bacteria detachment in this study. The sensitivity of the model parameters is temporally dynamic, emphasising the significance of conducting the sensitivity analysis across multiple time points. The surrogate models are shown to perform well, and produced ≈ 480 fold increase in computational efficiency. We conclude that a surrogate-based approach is effective, and resulting biofilm structure is determined primarily by a balance between bacteria growth, viscoelastic parameters and applied shear stress.

U2 - 10.1371/journal.pone.0195484

DO - 10.1371/journal.pone.0195484

M3 - Journal article

VL - 13

JO - PLoS ONE

JF - PLoS ONE

SN - 1932-6203

IS - 4

M1 - e0195484

ER -