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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

Automatic selection of segments and genes.
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fig5: Automatic selection of segments and genes.

Mentions: Once the data are represented, a CBR reasoning cycle is performed. During the retrieval phase, information regarding the catalogued genes and transcripts is recovered from the database. During the reuse phase, these genes are evaluated and valued according to the hypothesis contrast described in Section 3. After selecting the segments, their relevance can be observed. Figure 5 shows the information from the genes that were recovered from the database and considered to be relevant.


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)

Automatic selection of segments and genes.
© Copyright Policy
Related In: Results  -  Collection

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

fig5: Automatic selection of segments and genes.
Mentions: Once the data are represented, a CBR reasoning cycle is performed. During the retrieval phase, information regarding the catalogued genes and transcripts is recovered from the database. During the reuse phase, these genes are evaluated and valued according to the hypothesis contrast described in Section 3. After selecting the segments, their relevance can be observed. Figure 5 shows the information from the genes that were recovered from the database and considered to be relevant.

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