Title: Protein fold recognition with a two-layer method based on SVM-SA, WP-NN and C4.5 (TLM-SNC)

Authors: Mohammad Hossein Zangooei; Saeed Jalili

Addresses: SCS Lab, Computer Engineering Department, Electrical and Computer Engineering Faculty, Tarbiat Modares University, Tehran, Iran ' SCS Lab, Computer Engineering Department, Electrical and Computer Engineering Faculty, Tarbiat Modares University, Tehran, Iran

Abstract: The structural knowledge of protein is crucial in understanding its biological role. An effort is made to assign a fold to a given protein in a protein fold recognition problem. A computational Two-Layer Method (TLM) based on the Support Vector Machine (SVM), the Neural Network (NN) and the Decision Tree (C4.5) has been developed in this study for the assignment of a protein sequence to a folding class in SCOP. Prediction accuracy is measured on a dataset and the accuracy of the proposed method is very promising in comparison with other classification methods.

Keywords: protein fold recognition; bioinformatics; support vector machines; SVM; neural networks; C4.5; decision tree; proteins; protein structure; protein sequences; classification.

DOI: 10.1504/IJDMB.2013.055507

International Journal of Data Mining and Bioinformatics, 2013 Vol.8 No.2, pp.203 - 223

Received: 11 Oct 2011
Accepted: 16 Feb 2012
Published online: 20 Oct 2014 *

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