ArticleAlgorithms for molecular biology : AMB2018
FSH: fast spaced seed hashing exploiting adjacent hashes.
Article in Algorithms for molecular biology : AMB, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Hash functions in nucleotide sequence analysis.Genome research · 2026Review
- Efficient computation of spaced seed hashing with block indexing.BMC bioinformatics · 2018Article
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3 authors.
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Abstract
backgroundPatterns with wildcards in specified positions, namely
resultsThe method proposed in this paper, fast spaced-seed hashing (FSH), exploits the similarity of the hash values of spaced seeds computed at adjacent positions in the input sequence. In our experiments we compute the hash for each positions of metagenomics reads from several datasets, with respect to different spaced seeds. We also propose a generalized version of the algorithm for the simultaneous computation of multiple spaced seeds hashing. In the experiments, our algorithm can compute the hashing values of spaced seeds with a speedup, with respect to the traditional approach, between 1.6[Formula: see text] to 5.3[Formula: see text], depending on the structure of the spaced seed.
conclusionsSpaced seed hashing is a routine task for several bioinformatics application. FSH allows to perform this task efficiently and raise the question of whether other hashing can be exploited to further improve the speed up. This has the potential of major impact in the field, making spaced seed applications not only accurate, but also faster and more efficient. AVAILABILITY: The software FSH is freely available for academic use at: https://bitbucket.org/samu661/fsh/overview.
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