Mining DNA Sequence Patterns with Constraints Using Hybridization of Firefly and Group Search Optimization

Abstract

Abstract DNA sequence mining is essential in the study of the structure and function of the DNA sequence. A few exploration works have been published in the literature concerning sequence mining in information mining task. Similarly, in our past paper, an effective sequence mining was performed on a DNA database utilizing constraint measures and group search optimization (GSO). In that study, GSO calculation was utilized to optimize the sequence extraction process from a given DNA database. However, it is apparent that, occasionally, such an arbitrary seeking system does not accompany the optimal solution in the given time. To overcome the problem, we proposed in this work multiple constraints with hybrid firefly and GSO (HFGSO) algorithm. The complete DNA sequence mining process comprised the following three modules: (i) applying prefix span algorithm; (ii) calculating the length, width, and regular expression (RE) constraints; and (iii) optimal mining via HFGSO. First, we apply the concept of prefix span, which detects the frequent DNA sequence pattern using a prefix tree. Based on this prefix tree, length, width, and RE constraints are applied to handle restrictions. Finally, we adopt the HFGSO algorithm for the completeness of the mining result. The experimentation is carried out on the standard DNA sequence dataset, and the evaluation with DNA sequence dataset and the results show that our approach is better than the existing approach.