Modelos asociativos para la predicción de la localización subcelular de proteínas
Abstract
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.
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