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BioMed Research International
Volume 2015, Article ID 194624, 12 pages
http://dx.doi.org/10.1155/2015/194624
Research Article

aCGH-MAS: Analysis of aCGH by means of Multiagent System

1Biomedical Research Institute of Salamanca, BISITE Research Group, University of Salamanca, Edificio I+D+i, 37008 Salamanca, Spain
2IBMCC, Cancer Research Center, University of Salamanca-CSIC, 37007 Salamanca, Spain
3Department of Artificial Intelligence, Technical University of Madrid, Campus de Montegancedo, s/n Boadilla del Monte, 28660 Madrid, Spain

Received 21 August 2014; Revised 31 October 2014; Accepted 17 November 2014

Academic Editor: Juan M. Corchado

Copyright © 2015 Juan F. De Paz et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

There are currently different techniques, such as CGH arrays, to study genetic variations in patients. CGH arrays analyze gains and losses in different regions in the chromosome. Regions with gains or losses in pathologies are important for selecting relevant genes or CNVs (copy-number variations) associated with 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 multiagent system 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.