A Graph Clustering Approach to Weak Motif Recognition.

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. [ABSTRACT FROM AUTHOR]