Gene Expression Profiling Using Flexible Neural Trees

  • Yuehui Chen
  • Lizhi Peng
  • Ajith Abraham
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4224)


This paper proposes a Flexible Neural Tree (FNT) model for informative gene selection and gene expression profiles classification. Based on the pre-defined instruction/operator sets, a flexible neural tree model can be created and evolved. This framework allows input variables selection, over-layer connections and different activation functions for the various nodes involved. The FNT structure is developed using the Extended Compact Genetic Programming and the free parameters embedded in the neural tree are optimized by particle swarm optimization algorithm. Empirical results on two well-known cancer datasets shows competitive results with existing methods.


Particle Swarm Optimization Random Forest Informative Gene Global Good Position Leukemia Dataset 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yuehui Chen
    • 1
  • Lizhi Peng
    • 1
  • Ajith Abraham
    • 1
    • 2
  1. 1.School of Information Science and EngineeringJinan UniversityJinanP.R. China
  2. 2.IITA Professorship Program, School of Computer Science and Engg.Chung-Ang UniversitySeoulRepublic of Korea

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