دورية أكاديمية
A Bayesian non-parametric mixed-effects model of microbial growth curves.
| العنوان: | A Bayesian non-parametric mixed-effects model of microbial growth curves. |
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| المؤلفون: | Peter D Tonner, Cynthia L Darnell, Francesca M L Bushell, Peter A Lund, Amy K Schmid, Scott C Schmidler |
| المصدر: | PLoS Computational Biology, Vol 16, Iss 10, p e1008366 (2020) |
| بيانات النشر: | Public Library of Science (PLoS), 2020. |
| سنة النشر: | 2020 |
| المجموعة: | LCC:Biology (General) |
| مصطلحات موضوعية: | Biology (General), QH301-705.5 |
| الوصف: | 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 response under non-standard growth conditions. Here we develop a hierarchical Bayesian non-parametric model of population growth that identifies the latent growth behavior and response to perturbation, while simultaneously correcting for random effects in the data. This model enables more accurate estimates of the biological effect of interest, while better accounting for the uncertainty due to technical variation. Additionally, modeling hierarchical variation provides estimates of the relative impact of various confounding effects on measured population growth. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1553-734X 1553-7358 |
| Relation: | https://doaj.org/toc/1553-734X; https://doaj.org/toc/1553-7358 |
| DOI: | 10.1371/journal.pcbi.1008366 |
| URL الوصول: | https://doaj.org/article/bfd34c3824224212846d9bc76d435aaf |
| رقم الأكسشن: | edsdoj.bfd34c3824224212846d9bc76d435aaf |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 1553734X 15537358 |
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| DOI: | 10.1371/journal.pcbi.1008366 |