RPPMD (Randomly projected possible motif discovery): An efficient bucketing method for finding DNA planted Motif

Abstract

DNA contains the information of structure and function of different molecules of any living being. Short repeating patterns in a DNA sequence, called Motifs, are useful to understand and analyze this information. Recent advancements in gene expression analysis already prompt the scientists to introduce a number of motif finding algorithms. Among different motif search problems, one of them is Planted Motif Search (PMS). In this paper, we have proposed an approximate algorithm for Planted Motif Search which at first generates all possible motif set and use a bucketing concept to find out the proper motifs from the whole dataset. Two benchmark datasets of DNA sequences are used to evaluate the performance of the proposed method and its comparative analysis with other approaches. Experimental results demonstrate that proposed bucketing approach is more robust than the other approximate algorithms providing more amounts of motifs within less amount of time. Most of the time, above 80% of the possible motifs of the given input set are found within a reasonable time.