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An Efficient Multi-class Support Vector Machine Classifier for Protein Fold Recognition

  • Wiesław Chmielnicki
  • Katarzyna Sta̧por
  • Irena Roterman-Konieczna
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 74)

Abstract

Predicting the three-dimensional (3D) structure of a protein is a key problem in molecular biology. It is also interesting issue for statistical methods recognition. In this paper a multi-class Support Vector Machine (SVM) classifier is used on a real world data set. The SVM is a binary classifier and how to effectively extend a binary to the multi-class classifier case is still an on-going research problem. The new efficient approach is proposed in this paper. The obtained results are promising and reveal areas for possible further work.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Wiesław Chmielnicki
    • 1
  • Katarzyna Sta̧por
    • 2
  • Irena Roterman-Konieczna
    • 3
  1. 1.Faculty of Physics, Astronomy and Applied Computer Science 
  2. 2.Institute of Computer ScienceSilesian University 
  3. 3.Faculty of Medicine, Department of Bioinformatics and TelemedicineJagiellonian University 

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