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dc.contributor.authorDe Paz, Juan F. 
dc.contributor.authorBenito Sánchez, Rocío 
dc.contributor.authorBajo Pérez, Javier
dc.contributor.authorRodríguez Vicente, Ana E. 
dc.contributor.authorAbáigar Alvarado, María
dc.date.accessioned2017-09-05T10:59:21Z
dc.date.available2017-09-05T10:59:21Z
dc.date.issued2015
dc.identifier.citationJournal of Biomedicine and Biotechnology. Volumen 2015 (2015), pp. 1-12. Hindawi Publishing Corporation.
dc.identifier.issn1110-7243 (Online)
dc.identifier.urihttp://www.hindawi.com/journals/bmri/aip/194624/
dc.identifier.urihttp://hdl.handle.net/10366/134288
dc.description.abstractThere are currently different techniques, such as CGH Arrays, to study genetic variations in patients. Arrays CGH analyze gains and losses in different regions in the chromosomal. Regions with gains or losses in pathologies are important for selecting relevant genes, or CNVs (copy-number variations) associated to the variations detected within chromosomes. Information corresponding to mutations, genes, proteins, variations, CNVs and diseases can be found in different databases and it would be of interest to incorporate information of different sources to extract relevant information.. This work proposes a multi-agent to manage the information of aCGH arrays, with the aim of providing an intuitive and extensible system to analyze and interpret the results, . The agent roles integrate statistical techniques to select relevant variations and visualization techniques for the interpretation of the final results, and to extract relevant information from different sources of information by applying a CBR system.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherHindawi Publishing Corporation
dc.subjectComputer Science
dc.titleaCGH-MAS: Analysis of aCGH by Means of Multi-agent System
dc.typeinfo:eu-repo/semantics/article
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess


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