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发布时间：2019-03-09

论文类型：期刊论文

发表时间：2010-10-31

发表刊物：BMB REPORTS

收录刊物：Scopus、PubMed、SCIE

卷号：43

期号：10

页面范围：670-676

ISSN号：1976-6696

关键字：Elman neural network; Five-fold cross validation; Principal component analysis; Protein subcellular localization; Pseudo amino acid composition

摘要：In this paper, a novel approach, ELM-PCA, is introduced for the first time to predict protein subcellular localization. Firstly, Protein Samples are represented by the pseudo amino acid composition (PseAAC). Secondly, the principal component analysis (PCA) is employed to extract essential features. Finally, the Elman Recurrent Neural Network (RNN) is used as a classifier to identify the protein sequences. The results demonstrate that the proposed approach is effective and practical. [BMB reports 2010; 43(10): 670-6761