The increasing number of sequenced organisms has opened new possibilities for the computational discovery of cis-regulatory elements ('motifs') based on phylogenetic footprinting. Word-based, exhaustive approaches are among the best performing algorithms, however, they pose significant computational challenges as the number of candidate motifs to evaluate is very high. In this contribution, we describe a parallel, distributed-memory framework for de novo comparative motif discovery. Within this framework, two approaches for phylogenetic footprinting are implemented: an alignment-based and an alignment-free method. The framework is able to statistically evaluate the conservation of motifs in a search space containing over 160 million candidate motifs using a distributed-memory cluster with 200 CPU cores in a few hours. Software available from http://bioinformatics.intec.ugent.be/blsspeller/ © 2014 Springer-Verlag.
CITATION STYLE
De Witte, D., Van Bel, M., Audenaert, P., Demeester, P., Dhoedt, B., Vandepoele, K., & Fostier, J. (2014). A parallel, distributed-memory framework for comparative motif discovery. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8385 LNCS, pp. 268–277). Springer Verlag. https://doi.org/10.1007/978-3-642-55195-6_25
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