Comparing identification methods for DNA investigations of crimes and accidents

We examined an identifier matching problem, where an identifier corresponds to pieces of information extracted from DNA samples associated with crime suspects or victims of accidents. Such a sample is matched to cases of a database in order to identify a person. The data we used had been encoded as integers of relevantly small intervals. We solved the identifier matching task by sorting the data and then making comparisons for a maximally reduced subset of data produced by sorting. We first constructed a simple baseline method with exhaustive search, its optimised version and compared their results to those of the sort-based method, which was superior to the former two.