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Bio-kernel Self-organizing Map for HIV Drug Resistance Classification

  • Zheng Rong Yang
  • Natasha Young
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3610)

Abstract

Kernel self-organizing map has been recently studied by Fyfe and his colleagues [1]. This paper investigates the use of a novel bio-kernel function for the kernel self-organizing map. For verification, the application of the proposed new kernel self-organizing map to HIV drug resistance classification using mutation patterns in protease sequences is presented. The original self-organizing map together with the distributed encoding method was compared. It has been found that the use of the kernel self-organizing map with the novel bio-kernel function leads to better classification and faster convergence rate ...

Keywords

Protease Cleavage Site Support Vector Machine Approach Signal Peptide Cleavage Site Regularization Factor Protein Secondary Structure Prediction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Zheng Rong Yang
    • 1
  • Natasha Young
    • 1
  1. 1.Department of Computer ScienceUniversity of ExeterExeterUK

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