http://socictopen.socict.org/files/original/4a26d29824f351f61192ff9c180fdf98.pdf 3f63e84354ffeb8e581fe15f8572f68b 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 Gerbil: a fast and memory-efficient k-mer counter with GPU-support Creator An entity primarily responsible for making the resource Marius Erbert, Steffen Rechner, Matthias Müller-Hannemann Description An account of the resource Abstract Background A basic task in bioinformatics is the counting of k-mers in genome sequences. Existing k-mer counting tools are most often optimized for small k < 32 and suffer from excessive memory resource consumption or degrading performance for large k. However, given the technology trend towards long reads of next-generation sequencers, support for large k becomes increasingly important. Results We present the open source k-mer counting software Gerbil that has been designed for the efficient counting of k-mers for k ≥ 32. Our software is the result of an intensive process of algorithm engineering. It implements a two-step approach. In the first step, genome reads are loaded from disk and redistributed to temporary files. In a second step, the k-mers of each temporary file are counted via a hash table approach. In addition to its basic functionality, Gerbil can optionally use GPUs to accelerate the counting step. In a set of experiments with real-world genome data sets, we show that Gerbil is able to efficiently support both small and large k. Conclusions While Gerbil’s performance is comparable to existing state-of-the-art open source k-mer counting tools for small k < 32, it vastly outperforms its competitors for large k, thereby enabling new applications which require large values of k. Date A point or period of time associated with an event in the lifecycle of the resource 2017 Subject The topic of the resource k-mer counting, de novo assembly, Genome sequences, GPU computing, algorithm engineering Identifier An unambiguous reference to the resource within a given context DOI: 10.1186/s13015-017-0097-9 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