Accelerating motif discovery: motif matching on parallel hardware

Authors:
Geir Kjetil Sandve;Magnar Nedland;Øyvind Bø Syrstad;Lars Andreas Eidsheim;Osman Abul;Finn Drabløs
Affiliations:
Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway;Interagon A.S., Trondheim, Norway;Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway;Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway;Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway;Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
Venue:
WABI'06 Proceedings of the 6th international conference on Algorithms in Bioinformatics
Year:
2006

Citing 5
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Abstract

Discovery of motifs in biological sequences is an important problem, and several computational methods have been developed to date. One of the main limitations of the established motif discovery methods is that the running time is prohibitive for very large data sets, such as upstream regions of large sets of cell-cycle regulated genes. Parallel versions have been developed for some of these methods, but this requires supercomputers or large computer clusters. Here, we propose and define an abstract module PAMM (Parallel Acceleration of Motif Matching) with motif matching on parallel hardware in mind. As a proof-of-concept, we provide a concrete implementation of our approach called MAMA. The implementation is based on the MEME algorithm, and uses an implementation of PAMM based on specialized hardware to accelerate motif matching. Running MAMA on a standard PC with specialized hardware on a single PCI-card compares favorably to running parallel MEME on a cluster of 12 computers.