A Bayesian non-parametric mixed-effects model of microbial growth curves.

ABSTRACT: Substantive changes in gene expression, metabolism, and the proteome are manifested in overall changes in microbial population growth. Quantifying how microbes grow is therefore fundamental to areas such as genetics, bioengineering, and food safety. Traditional parametric growth curve models capture the population growth behavior through a set of summarizing parameters. However, estimation of these parameters from data is confounded by random effects such as experimental variability, batch effects or differences in experimental material. A systematic statistical method to identify and correct for such confounding effects in population growth data is not currently available. Further, our previous work has demonstrated that parametric models are insufficient to explain and predict microbial

SUBMITTER: Tonner PD 

PROVIDER: S-EPMC7644099 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature