Prediction of Protein Subcellular Localization Using EDA based Ensemble Classifiers
Автор: Ying Li
Журнал: International Journal of Engineering and Manufacturing(IJEM) @ijem
Статья в выпуске: 6 vol.1, 2011 года.
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The function of protein is closely correlated with its subcellular locations. New composed proteins can perform normal biological function only after they are translocated to correct subcellular locations. In this paper, a new selective ensemble classifiers based on EDA algorithm has been proposed. In the method, pseudo amino acid composition was firstly applied to form the protein feature sets, then 10 neural networks is generated to learn the subsets which are re-sampling from feature subsets with PSO algorithm. At last, appropriate classifiers are selected to construct the prediction committee with EDA algorithm. Experiment shows that the proposed method produces the best prediction accuracy than the other methods on SNL6 database.
Protein subcellular location, Estimation of Distribution Algorithm (EDA), selective ensemble, Pseudo amino acid composition
Короткий адрес: https://sciup.org/15014245
IDR: 15014245
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