Efficient string matching: an aid to bibliographic search
Communications of the ACM
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
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
Fundamenta Informaticae - Special issue on computing patterns in strings
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
Optimizing Multiple Seeds for Protein Homology Search
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Good spaced seeds for homology search
Bioinformatics
Optimal spaced seeds for hidden Markov models, with application to homologous coding regions
CPM'03 Proceedings of the 14th annual conference on Combinatorial pattern matching
Superiority of Spaced Seeds for Homology Search
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Optimal probing patterns for sequencing by hybridization
WABI'06 Proceedings of the 6th international conference on Algorithms in Bioinformatics
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We propose a general approach to compute the seed sensitivity, that can be applied to different definitions of seeds. It treats separately three components of the seed sensitivity problem – a set of target alignments, an associated probability distribution, and a seed model – that are specified by distinct finite automata. The approach is then applied to a new concept of subset seeds for which we propose an efficient automaton construction. Experimental results confirm that sensitive subset seeds can be efficiently designed using our approach, and can then be used in similarity search producing better results than ordinary spaced seeds.