An Automaton for Motifs Recognition in DNA Sequences

In this paper we present a new algorithm to find inexact motifs (which are transformed into a set of exact subsequences) from a DNA sequence. Our algorithm builds an automaton that searches for the set of exact subsequences in the DNA database (that can be very long). It starts with a preprocessing phase in which it builds the finite automaton, in this phase it also considers the case in which two di erent subsequences share a substring (in other words, the subsequences might overlap), this is implemented in a similar way as the KMP algorithm. During the searching phase, the algorithm recognizes all instances in the set of input subsequences that appear in the DNA sequence. The automaton is able to perform the search phase in linear time with respect to the dimension of the input sequence. Experimental results show that the proposed algorithm performs better than the Aho-Corasick algorithm, which has been proved to perform better than the naive approach, even more; it is considered to run in linear time.