The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
A fast string searching algorithm
Communications of the ACM
Efficient string matching: an aid to bibliographic search
Communications of the ACM
Accelerating Protein Classification Using Suffix Trees
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
Computing exact P-values for DNA motifs
Bioinformatics
Bioinformatics
Self-overlapping Occurrences and Knuth-Morris-Pratt Algorithm for Weighted Matching
LATA '09 Proceedings of the 3rd International Conference on Language and Automata Theory and Applications
Bioinformatics
Optimizing data intensive GPGPU computations for DNA sequence alignment
Parallel Computing
Parallel Position Weight Matrices Algorithms
ISPDC '09 Proceedings of the 2009 Eighth International Symposium on Parallel and Distributed Computing
Bioinformatics
Fast search algorithms for position specific scoring matrices
BIRD'07 Proceedings of the 1st international conference on Bioinformatics research and development
Pattern Recognition Letters
GPU-ClustalW: using graphics hardware to accelerate multiple sequence alignment
HiPC'06 Proceedings of the 13th international conference on High Performance Computing
Initial experiences porting a bioinformatics application to a graphics processor
PCI'05 Proceedings of the 10th Panhellenic conference on Advances in Informatics
Large scale matching for position weight matrices
CPM'06 Proceedings of the 17th Annual conference on Combinatorial Pattern Matching
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Position Weight Matrices (PWMs) are broadly used in computational biology. The basic problems, Scan and MultipleScan, aim to find all the occurrences of a given PWM or a set of PWMs in long sequences. Some other PWM tasks share a common NP-hard subproblem, ScoreDistribution. The existing algorithms rely on the enumeration on a large set of scores or words, and they are mostly not suitable for parallelization. We propose a new algorithm, BucketScoreDistribution, that is both very efficient and suitable for parallelization. We bound the error induced by this algorithm. We realized a GPU prototype for Scan, MultipleScan and BucketScoreDistribution with the CUDA libraries, and report for the different problems speedups larger than 10x on several Nvidia cards.