Matrix computations (3rd ed.)
Designing seeds for similarity search in genomic DNA
RECOMB '03 Proceedings of the seventh annual international conference on Research in computational molecular biology
Better Filtering with Gapped q-Grams
CPM '01 Proceedings of the 12th Annual Symposium on Combinatorial Pattern Matching
Designing multiple simultaneous seeds for DNA similarity search
RECOMB '04 Proceedings of the eighth annual international conference on Resaerch in computational molecular biology
Sensitivity analysis and efficient method for identifying optimal spaced seeds
Journal of Computer and System Sciences
On spaced seeds for similarity search
Discrete Applied Mathematics
Estimating Seed Sensitivity on Homogeneous Alignments
BIBE '04 Proceedings of the 4th IEEE Symposium on Bioinformatics and Bioengineering
Efficient Methods for Generating Optimal Single and Multiple Spaced Seeds
BIBE '04 Proceedings of the 4th IEEE Symposium on Bioinformatics and Bioengineering
Efficient randomized pattern-matching algorithms
IBM Journal of Research and Development - Mathematics and computing
Good spaced seeds for homology search
Bioinformatics
Superiority and complexity of the spaced seeds
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Amino Acid Classification and Hash Seeds for Homology Search
BICoB '09 Proceedings of the 1st International Conference on Bioinformatics and Computational Biology
Seed optimization for i.i.d. similarities is no easier than optimal Golomb ruler design
Information Processing Letters
Masking patterns in sequences: A new class of motif discovery with don't cares
Theoretical Computer Science
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Homology search finds similar segments between two biological sequences, such as DNA or protein sequences. A significant fraction of computing power in the world is dedicated to performing such tasks. The introduction of optimal spaced seeds by Ma et al. has increased both the sensitivity and the speed of homology search and it has been adopted by many alignment programs such as BLAST. With the further improvement provided by multiple spaced seeds in PatternHunterII, the sensitivity of dynamic programming is approached at BLASTn speed. Whereas computing optimal multiple spaced seeds was proved to be NP-hard, we show that, from practical point of view, computing good ones can be very efficient. We give a simple heuristic algorithm which computes good multiple seeds in polynomial time. Computing sensitivity is not required. When allowing the computation of the sensitivity for few seeds, we obtain better multiple seeds than previous ones in much shorter time.