A Bayesian approach to analyzing phenotype microarray data enables estimation of microbial growth parameters

Gerstgrasser, Matthias; Nicholls, Sarah; Stout, Michael; Smart, Katherine; Powell, Chris; Kypraios, Theodore; Stekel, Dov J.

doi:10.1142/S0219720016500074

All Outputs (2)

Production of Baker's yeast using seawater-based media (2016)
Journal Article
Kyyaly, M. A., Zaky, A. S., & Powell, C. D. (2016). Production of Baker's yeast using seawater-based media. New Biotechnology, 33(Supp.), Article S71. https://doi.org/10.1016/j.nbt.2016.06.963

A Bayesian approach to analyzing phenotype microarray data enables estimation of microbial growth parameters (2016)
Journal Article
Gerstgrasser, M., Nicholls, S., Stout, M., Smart, K., Powell, C., Kypraios, T., & Stekel, D. J. (2016). A Bayesian approach to analyzing phenotype microarray data enables estimation of microbial growth parameters. Journal of Bioinformatics and Computational Biology, 14(03), 1-23. https://doi.org/10.1142/S0219720016500074

Biolog phenotype microarrays enable simultaneous, high throughput analysis of cell cultures in different environments. The output is high-density time-course data showing redox curves (approximating growth) for each experimental condition. The softwa... Read More about A Bayesian approach to analyzing phenotype microarray data enables estimation of microbial growth parameters.