An Artificial Immune System for Evolving Amino Acid Clusters Tailored to Protein Function Prediction

  • A. Secker
  • M. N. Davies
  • A. A. Freitas
  • J. Timmis
  • E. Clark
  • D. R. Flower
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5132)


This paper addresses the classification task of data mining (a form of supervised learning) in the context of an important bioinformatics problem, namely the prediction of protein functions. This problem is cast as a hierarchical classification problem, where the protein functions to be predicted correspond to classes that are arranged in a hierarchical structure, in the form of a class tree. The main contribution of this paper is to propose a new Artificial Immune System that creates a new representation for proteins, in order to maximize the predictive accuracy of a hierarchical classification algorithm applied to the corresponding protein function prediction problem.


artificial immune systems data mining bioinformatics classification clustering 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • A. Secker
    • 1
  • M. N. Davies
    • 2
  • A. A. Freitas
    • 1
  • J. Timmis
    • 3
  • E. Clark
    • 3
  • D. R. Flower
    • 2
  1. 1.Computing Laboratory and Centre for BioMedical InformaticsUniversity of KentCanterburyUK
  2. 2.The Jenner InstituteUniversity of OxfordCompton, NewburyUK
  3. 3.Departments of Computer Science and ElectronicsUniversity of YorkYorkUK

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