A graph clustering approach to weak motif recognition

Authors:
Christina Boucher;Daniel G. Brown;Paul Church
Affiliations:
D. R. Cheriton School of Computer Science, University of Waterloo;D. R. Cheriton School of Computer Science, University of Waterloo;D. R. Cheriton School of Computer Science, University of Waterloo
Venue:
WABI'07 Proceedings of the 7th international conference on Algorithms in Bioinformatics
Year:
2007

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Abstract

The aim of the motif recognition problem is to detect a set of mutually similar subsequences in a collection of biological sequences. Weak motif recognition is where the sequences are highly degenerate. Our new approach to this problem uses a weighted graph model and a heuristic that determines high weight subgraphs in polynomial time. Our experimental tests show impressive accuracy and efficiency. We give results that demonstrate a theoretical dichotomy between cliques in our graph that represent actual motifs and those that do not.