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dc.contributor.authorLópez-Fernández, Aurelio
dc.contributor.authorGómez-Vela, Francisco A.
dc.contributor.authorGonzález-Domínguez, Jorge
dc.contributor.authorBidare-Divakarachari, Parameshachari
dc.date.accessioned2024-02-23T11:08:10Z
dc.date.available2024-02-23T11:08:10Z
dc.date.issued2024
dc.identifier.citationA. López-Fernández, F. A. Gómez-Vela, J. Gonzalez-Dominguez, and P. Bidare-Divakarachari, "bioScience: A new python science library for high-performance computing bioinformatics analytics", SoftwareX, Vol. 26, art. 101666, May 2024, https://doi.org/10.1016/j.softx.2024.101666es_ES
dc.identifier.urihttp://hdl.handle.net/2183/35712
dc.descriptionFinanciado para publicación en acceso aberto: Universidad Pablo de Olavide/CBUAes_ES
dc.description.abstract[Abstract]: BioScience is an advanced Python library designed to satisfy the growing data analysis needs in the field of bioinformatics by leveraging High-Performance Computing (HPC). This library encompasses a vast multitude of functionalities, from loading specialized gene expression datasets (microarrays, RNA-Seq, etc.) to preprocessing techniques and data mining algorithms suitable for this type of datasets. BioScience is distinguished by its capacity to manage large amounts of biological data, providing users with efficient and scalable tools for the analysis of genomic and transcriptomic data through the use of parallel architectures for clusters composed of CPUs and GPUs.es_ES
dc.language.isoenges_ES
dc.publisherElsevier Ltdes_ES
dc.relation.urihttps://doi.org/10.1016/j.softx.2024.101666es_ES
dc.rightsAtribución 4.0 Internacional (CC BY)es_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectBioinformaticses_ES
dc.subjectHigh-performance computinges_ES
dc.subjectData sciencees_ES
dc.subjectData mininges_ES
dc.subjectData analysises_ES
dc.titlebioScience: A new python science library for high-performance computing bioinformatics analyticses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleSoftwareXes_ES
UDC.volume26es_ES
UDC.issue101666es_ES
dc.identifier.doi10.1016/j.softx.2024.101666


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