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dc.contributor.authorCorchado Rodríguez, Juan Manuel 
dc.contributor.authorBichindaritz, Isabelle
dc.contributor.authorDe Paz, Juan F. 
dc.date.accessioned2017-09-05T10:59:25Z
dc.date.available2017-09-05T10:59:25Z
dc.date.issued2015
dc.identifier.citationBioMed Research International. Volumen 2015 (2015), pp. 1-2. Hindawi Publishing Corporation.
dc.identifier.issn2314-6133
dc.identifier.urihttp://hdl.handle.net/10366/134294
dc.description.abstractThe increased volume of existing information on biological processes and the use of large databases have significantly increased the accessibility of datasets to the scientific community. This has enabled performing an analysis to facilitate the extraction of relevant information or modeling and optimizing tasks in different processes. Parallel to the increasing volumes of information is the emergence of new or adapted distributed computing models such as grid computing and cloud computing. These management systems along with new techniques of artificial intelligence, or more specifically knowledge discovery, are making it possible to perform an analysis of the information in a more efficient manner and are enabling the creation of adaptive systems with learning ability.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherHindawi Publishing Corporation
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectComputer Science
dc.titleDistributed Artificial Intelligence Models for Knowledge Discovery in Bioinformatics
dc.typeinfo:eu-repo/semantics/article
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess


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