Consensus Pattern Selection from Structured Profile using Multiobjective Algorithm

Abstract

Consensus are also referred as motif. Motif detection is a demanding task in bioinformatics and the broad variance of protein motifs make it challenging. Imprinting gapped motifs is very important but tedious because of feasible combinatorial representations caused by considering long gaps.Detection of planted (l, d) motif is an NP complete problem. We propose a new method to identify motif by Markov clustering of the Augmented Emerging Substrings (MAES). In this, we generate augmented bucket with pareto optimization by considering the multiplicity and weight of each node and detail the emerging substrings.Experimental outcome on simulated data exhibits that i) MAES is able to identify(l,d) motifs effectively and is absolutely faster than contemporary state of art (l,d) motif uncovering algorithm like F-motif and MEME-ChIP ii) MAES is able to identify subtle patterns that are concealed by stronger pattern in data.