SAICSIT '04 Proceedings of the 2004 annual research conference of the South African institute of computer scientists and information technologists on IT research in developing countries
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)
Superiority and complexity of the spaced seeds
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
On the complexity of the spaced seeds
Journal of Computer and System Sciences
Hardness of optimal spaced seed design
Journal of Computer and System Sciences
Amino Acid Classification and Hash Seeds for Homology Search
BICoB '09 Proceedings of the 1st International Conference on Bioinformatics and Computational Biology
A minimum cost process in searching for a set of similar DNA sequences
TELE-INFO'06 Proceedings of the 5th WSEAS international conference on Telecommunications and informatics
A combinatorial framework for designing (pseudoknotted) RNA algorithms
WABI'11 Proceedings of the 11th international conference on Algorithms in bioinformatics
Optimal spaced seeds for faster approximate string matching
ICALP'05 Proceedings of the 32nd international conference on Automata, Languages and Programming
Rapid homology search with two-stage extension and daughter seeds
COCOON'05 Proceedings of the 11th annual international conference on Computing and Combinatorics
A unifying framework for seed sensitivity and its application to subset seeds
WABI'05 Proceedings of the 5th International conference on Algorithms in Bioinformatics
Fast computation of good multiple spaced seeds
WABI'07 Proceedings of the 7th international conference on Algorithms in Bioinformatics
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We address the problem of estimating the sensitivity ofseed-based similarity search algorithms. In contrast to approachesbased on Markov models [Faster and more sensitive homology search, Designing seeds for similarity search in genomic DNA, Optimal spaced seeds for Hidden Markov Models, with application to homologous coding regions, Vector seeds: an extension to spaced seeds allows substantial improvements in sensitivity and specificity, Sensitivity analysis and efficient method for identifying optimal spaced seeds], we studythe estimation based on homogeneous alignments. We describean algorithm for counting and random generation ofthose alignments and an algorithm for exact computation ofthe sensitivity for a broad class of seed strategies. We provideexperimental results demonstrating a bias introducedby ignoring the homogeneousness condition.