Modelling the growth domain of Clostridium botulinum via kernel survival analysis

Foxall, R. J., Cawley, G. C. and Peck, M. W. (2003) Modelling the growth domain of Clostridium botulinum via kernel survival analysis. In: Proceedings of the IEEE/INNS International Joint Conference on Artificial Neural Networks (IJCNN-2003), 2003-07-20 - 2003-07-24.

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Abstract

Clostridium botulinum is a bacterium present in the raw ingredients of many foods. It produces a powerful neurotoxin as part of its growth process, that can prove fatal when doses as small as 30ng are consumed. It is therefore vital to be able to accurately determine the food processing and storage conditions where toxin production is possible, known as the "growth domain". This paper describes a new approach to modelling the growth domain of microbial pathogens, by constructing a regularised kernel model relating heat treatment and subsequent incubation conditions to the parameters of a statistical distribution modelling the probability of growth as a function of incubation time. We demonstrate that the use of the "kernel trick" permits the extension of methods from classical survival analysis to account for non-linear dependencies in a principled manner.

Item Type: Conference or Workshop Item (Paper)
Faculty \ School: Faculty of Science > School of Computing Sciences

University of East Anglia > Faculty of Science > Research Groups > Computational Biology (subgroups are shown below) > Machine learning in computational biology
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Depositing User: Vishal Gautam
Date Deposited: 04 Jul 2011 08:14
Last Modified: 12 May 2020 00:21
URI: https://ueaeprints.uea.ac.uk/id/eprint/23228
DOI: 10.1109/IJCNN.2003.1224041

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