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. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Boucher, C., Brown, D. G., & Church, P. (2007). A graph clustering approach to weak motif recognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4645 LNBI, pp. 149–160). Springer Verlag. https://doi.org/10.1007/978-3-540-74126-8_14
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