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aCGH-MAS: analysis of aCGH by means of multiagent system.

De Paz JF, Benito R, Bajo J, Rodríguez AE, Abáigar M - Biomed Res Int (2015)

Bottom Line: CGH arrays analyze gains and losses in different regions in the chromosome.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.

View Article: PubMed Central - PubMed

Affiliation: Biomedical Research Institute of Salamanca, BISITE Research Group, University of Salamanca, Edificio I+D+i, 37008 Salamanca, Spain.

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.

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Related in: MedlinePlus

Multiagent system architecture.
© Copyright Policy - open-access
Related In: Results  -  Collection


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fig1: Multiagent system architecture.

Mentions: The multiagent system is composed of three layers: analysis, information management, and visualization. Figure 1 shows the multiagent system architecture and the layers it comprises. The analysis layer performs the microarray analysis. It includes several algorithms that can be applied to the specific case study taken into consideration. The information management layer generates a local database using the information of several sources. The visualization layer manages the information and the algorithms. It displays the information and the results obtained after applying the existing algorithms at the analysis layer.


aCGH-MAS: analysis of aCGH by means of multiagent system.

De Paz JF, Benito R, Bajo J, Rodríguez AE, Abáigar M - Biomed Res Int (2015)

Multiagent system architecture.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4385609&req=5

fig1: Multiagent system architecture.
Mentions: The multiagent system is composed of three layers: analysis, information management, and visualization. Figure 1 shows the multiagent system architecture and the layers it comprises. The analysis layer performs the microarray analysis. It includes several algorithms that can be applied to the specific case study taken into consideration. The information management layer generates a local database using the information of several sources. The visualization layer manages the information and the algorithms. It displays the information and the results obtained after applying the existing algorithms at the analysis layer.

Bottom Line: CGH arrays analyze gains and losses in different regions in the chromosome.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.

View Article: PubMed Central - PubMed

Affiliation: Biomedical Research Institute of Salamanca, BISITE Research Group, University of Salamanca, Edificio I+D+i, 37008 Salamanca, Spain.

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.

Show MeSH
Related in: MedlinePlus