Artificial Immune System for Classification of Cancer

  • Shin Ando
  • Hitoshi Iba
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2611)


This paper presents a method for cancer type classification based on microarray-monitored data. The method is based on artificial immune system(AIS), which utilizes immunological recognition for classification. The system evolutionarily selects important genes; optimize their weights to derive classification rules. This system was applied to gene expression data of acute leukemia patients to classify their cancer class. The primary result found few classification rules which correctly classified all the test samples and gave some interesting implications for feature selection principles.


Support Vector Machine Training Sample Gene Expression Data Memory Cell Negative Selection 
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 2003

Authors and Affiliations

  • Shin Ando
    • 1
  • Hitoshi Iba
    • 2
  1. 1.Dept. of Electronics EngineeringSchool of Engineering University of TokyoJapan
  2. 2.Dept. of Frontier Informatics, School of Frontier ScienceUniversity of TokyoJapan

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