Journal of Data Science

Abstract: DNA fingerprinting is a microbiological technique widely used to find a DNA sequence specific for a microbe. It involves slicing the genomes of the microbe into DNA fragments with manageable sizes, sorting the DNA pieces by length and finally identifying a DNA sequence unique to the mi crobe, using probe-based assays. This unique DNA is referred to as DNA fingerprint of the microbe under study. In this paper, we introduce a proba bilistic model to estimate the chance of identifying the DNA fingerprint from the genome of a microbe when the DNA fingerprinting method is employed. We derive a closed-form functional relationship between the chance of find ing the fingerprint and factors that can be experimentally controlled either in part, fully or not at all. Because the odds of finding a specific DNA fin gerprint can only be improved by experimental design to a certain degree, in a broader sense, we show that the discovery of a DNA fingerprint is a process governed more by chance than by design. Nevertheless, the results can be potentially used to guide experiments in maximizing the chance of finding a DNA fingerprint of interest.