International audienceSeveral algorithms for similarity search employ seeding techniques to quickly discard very dissimilar regions. In this paper, we study theoretical properties of lossless seeds, i.e., spaced seeds having full sensitivity. We prove that lossless seeds coincide with languages of certain sofic subshifts, hence they can be recognized by finite automata. Moreover, we show that these subshifts are fully given by the number of allowed errors k and the seed margin ℓ. We also show that for a fixed k, optimal seeds must asymptotically satisfy ℓ ∈ Q(m^(k/k+1))
International audienceWe propose a general approach to compute the seed sensitivity, that can be app...
We address the problem of estimating the sensitivity of seed-based similarity search algorithms. In ...
We address the problem of estimating the sensitivity of seed-based similarity search algorithms. In ...
Several algorithms for similarity search employ seeding techniques to quickly discard very dissimila...
International audienceSeveral algorithms for similarity search employ seeding techniques to quickly ...
Spaced seeds are used in approximate pattern matching algorithms to quickly discard regions where a ...
We propose a general approach to compute the seed sensitivity, that can be applied to different def...
We propose a general approach to compute the seed sensitivity, that can be applied to different defi...
We propose a general approach to compute the seed sensitivity, that can be applied to different defi...
Spaced seeds are a fundamental tool for similarity search in biosequences. The best sensitivity/sele...
International audienceWe address the problem of approximate pattern matching using the Levenshtein d...
International audienceApproximate pattern matching is an important computational problem that has a ...
AbstractSpeeding up approximate pattern matching is a line of research in stringology since the 80s....
Filtering is a standard technique for fast approximate string matching in practice. In filtering, a ...
AbstractFiltering is a standard technique for fast approximate string matching in practice. In filte...
International audienceWe propose a general approach to compute the seed sensitivity, that can be app...
We address the problem of estimating the sensitivity of seed-based similarity search algorithms. In ...
We address the problem of estimating the sensitivity of seed-based similarity search algorithms. In ...
Several algorithms for similarity search employ seeding techniques to quickly discard very dissimila...
International audienceSeveral algorithms for similarity search employ seeding techniques to quickly ...
Spaced seeds are used in approximate pattern matching algorithms to quickly discard regions where a ...
We propose a general approach to compute the seed sensitivity, that can be applied to different def...
We propose a general approach to compute the seed sensitivity, that can be applied to different defi...
We propose a general approach to compute the seed sensitivity, that can be applied to different defi...
Spaced seeds are a fundamental tool for similarity search in biosequences. The best sensitivity/sele...
International audienceWe address the problem of approximate pattern matching using the Levenshtein d...
International audienceApproximate pattern matching is an important computational problem that has a ...
AbstractSpeeding up approximate pattern matching is a line of research in stringology since the 80s....
Filtering is a standard technique for fast approximate string matching in practice. In filtering, a ...
AbstractFiltering is a standard technique for fast approximate string matching in practice. In filte...
International audienceWe propose a general approach to compute the seed sensitivity, that can be app...
We address the problem of estimating the sensitivity of seed-based similarity search algorithms. In ...
We address the problem of estimating the sensitivity of seed-based similarity search algorithms. In ...