Food microbiology has been applying mathematical concepts and computational techniques at an increasing rate. One reason for this is the growing demand to analyze vast amounts of microbiology data, whose quality has greatly improved due to better and better measuring systems. Another reason is the progress in developing mathematical, computational means to process those data. The application of powerful computational tools has had a key role in the evolution of predictive food microbiology. ComBase, the No.l database of bacterial responses to food environments introduced in this paper, is an example how the computational and mathematical tools have strengthened each other during the last two decades.
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