https://www.socictopen.socict.org/files/original/410b0c65ed4a369860cebbe0d2f51618.pdf 8de2b71856d8a8fad97e3becc0e7ea44 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource FSH: fast spaced seed hashing exploiting adjacent hashes Creator An entity primarily responsible for making the resource Samuele Girotto, Matteo Comin, Cinzia Pizzi Description An account of the resource Abstract Background Patterns with wildcards in specified positions, namely spaced seeds, are increasingly used instead of k-mers in many bioinformatics applications that require indexing, querying and rapid similarity search, as they can provide better sensitivity. Many of these applications require to compute the hashing of each position in the input sequences with respect to the given spaced seed, or to multiple spaced seeds. While the hashing of k-mers can be rapidly computed by exploiting the large overlap between consecutive k-mers, spaced seeds hashing is usually computed from scratch for each position in the input sequence, thus resulting in slower processing. Results The 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$$\times$$ × to 5.3$$\times$$ × , depending on the structure of the spaced seed. Conclusions Spaced 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. Date A point or period of time associated with an event in the lifecycle of the resource 2018 Subject The topic of the resource Spaced seeds, Kmers, Efficient hashing Identifier An unambiguous reference to the resource within a given context DOI: 10.1186/s13015-018-0125-4 Source A related resource from which the described resource is derived Algorithms for Molecular Biology Publisher An entity responsible for making the resource available BMC Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Biology (General), Genetics Language A language of the resource EN