@inbook{ebe3aa5fc3dc4db2b0ab1a6acd9590aa,

title = "A hierarchical model to predict the probability of germination of bacterial spores",

abstract = "Statistical hierarchical modelling is a powerful strategy to model complicated processes by a sequence of relatively simple models placed in a hierarchy. A hierarchical model includes the specification of the conditional probability density functions of response variables given candidate predictor variables, along with the specification of the probability density function of each single variable. We developed a statistical hierarchical model of the probability that a bacterial spore germinates, and used this model to predict the number of germinant spores as function of number of bacterial cells, nutrients concentration and amount of germination activation agents.",

keywords = "C. botulinum, Hierarchical models, bacterial sporulation and germination",

author = "Paola Lecca and Angela Re and Barker, {Gary C.} and Ihekwaba, {Adaoha E.C.}",

year = "2017",

month = oct,

day = "5",

doi = "10.1109/CIBCB.2017.8058560",

language = "English",

isbn = "978-1-4673-8989-1",

series = "2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1--7",

booktitle = "2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2017",

address = "United States",

}