A Novel Hybrid GA/RBFNN Technique for Protein Sequences Classification

Xing-Ming      Zhao; De-Shuang      Huang; Yiu-ming      Cheung

doi:10.2174/0929866053765707

Abstract

A novel hybrid genetic algorithm (GA)/radial basis function neural network (RBFNN) technique, which selects features from the protein sequences and trains the RBF neural network simultaneously, is proposed in this paper. Experimental results show that the proposed hybrid GA/RBFNN system outperforms the BLAST and the HMMer.

Keywords: protein sequences classification, hybrid ga/rbfnn method, feature selection

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Protein & Peptide Letters

Title: A Novel Hybrid GA/RBFNN Technique for Protein Sequences Classification

Volume: 12 Issue: 4

Author(s): Xing-Ming Zhao, De-Shuang Huang and Yiu-ming Cheung

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Keywords: protein sequences classification, hybrid ga/rbfnn method, feature selection

Abstract: A novel hybrid genetic algorithm (GA)/radial basis function neural network (RBFNN) technique, which selects features from the protein sequences and trains the RBF neural network simultaneously, is proposed in this paper. Experimental results show that the proposed hybrid GA/RBFNN system outperforms the BLAST and the HMMer.

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Zhao Xing-Ming, Huang De-Shuang and Cheung Yiu-ming, A Novel Hybrid GA/RBFNN Technique for Protein Sequences Classification, Protein & Peptide Letters 2005; 12 (4) . https://dx.doi.org/10.2174/0929866053765707