Efficient Ensemble Schemes for Protein Secondary Structure Prediction

Kun-Hong      Liu; Jun-Feng      Xia; Xueling      Li

doi:10.2174/092986608784567546

Abstract

This paper proposes an efficient ensemble system to tackle the protein secondary structure prediction problem with neural networks as base classifiers. The experimental results show that the multi-layer system can lead to better results. When deploying more accurate classifiers, the higher accuracy of the ensemble system can be obtained.

Keywords: Protein secondary structure prediction, neural network, multiple sequence alignment, classifier ensemble system

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Protein & Peptide Letters

Title: Efficient Ensemble Schemes for Protein Secondary Structure Prediction

Volume: 15 Issue: 5

Author(s): Kun-Hong Liu, Jun-Feng Xia and Xueling Li

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Keywords: Protein secondary structure prediction, neural network, multiple sequence alignment, classifier ensemble system

Abstract: This paper proposes an efficient ensemble system to tackle the protein secondary structure prediction problem with neural networks as base classifiers. The experimental results show that the multi-layer system can lead to better results. When deploying more accurate classifiers, the higher accuracy of the ensemble system can be obtained.

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Liu Kun-Hong, Xia Jun-Feng and Li Xueling, Efficient Ensemble Schemes for Protein Secondary Structure Prediction, Protein & Peptide Letters 2008; 15 (5) . https://dx.doi.org/10.2174/092986608784567546