Serviços Personalizados
Journal
Artigo
Indicadores
Citado por SciELO
Acessos
Links relacionados
Similares em SciELO
Compartilhar
Revista mexicana de ingeniería biomédica
versão On-line ISSN 2395-9126versão impressa ISSN 0188-9532
Resumo
ACEVEDO-MOSQUEDA, ME; ACEVEDO-MOSQUEDA, MA e CALDERON-SAMBARINO, MJ. Associative models for the prediction of proteins subcellular localization. Rev. mex. ing. bioméd [online]. 2012, vol.33, n.1, pp.17-28. ISSN 2395-9126.
Protein subcellular localization is fundamental for understanding its biological function. Proteins are transported to specified cellular elements before they are synthesized. They are part of cellular activity and their function is efficient when they are in the right place. Therefore, genes (codified as proteins) localization into the cell becomes a key task. In this work, a method to localize automatically proteins into the cell is presented; as a particular case, the method was applied to the dataset GENES. The proposal has an associative approach and the specific model of alpha-beta associative multi-memories is applied. The effectiveness of the model was of 97.99%, which means that from 748 genes, the method was not able to localize 14 genes.
Palavras-chave : Prediction; subcellular localization; associative models; alpha-beta multimemories.