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dc.contributor.authorGonzález, Roberto
dc.contributor.authorZato Domínguez, Davinia Carolina 
dc.contributor.authorBenito Sánchez, Rocío 
dc.contributor.authorHernández, María
dc.contributor.authorHernández Rivas, Jesús María 
dc.contributor.authorDe Paz, Juan F. 
dc.date.accessioned2017-09-06T09:14:10Z
dc.date.available2017-09-06T09:14:10Z
dc.date.issued2012
dc.identifier.citationAdvances in Intelligent and Soft Computing 6th International Conference on Practical Applications of Computational Biology & Bioinformatics. pp. 209-216.
dc.identifier.issnhttp://id.crossref.org/isbn/978-3-642-28838-8(Print)/ http://id.crossref.org/isbn/978-3-642-28839-5(Online)
dc.identifier.urihttp://dx.doi.org/10.1007/978-3-642-28839-5_24
dc.identifier.urihttp://hdl.handle.net/10366/134848
dc.description.abstractAdvances in bioinformatics have contributed towards a significant increase in available information. Information analysis requires the use of distributed computing systems to best engage the process of data analysis. This study proposes a multiagent system that incorporates grid technology to facilitate distributed data analysis by dynamically incorporating the roles associated to each specific case study. The system was applied to genetic sequencing data to extract relevant information about insertions, deletions or polymorphisms.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherSpringer Science + Business Media
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectComputer Science
dc.titleSAMasGC: Sequencing Analysis with a Multiagent System and Grid Computing
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess


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Attribution-NonCommercial-NoDerivs 3.0 Unported
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Unported