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  • Research Article
  • Open Access

Detect Key Gene Information in Classification of Microarray Data

EURASIP Journal on Advances in Signal Processing20082008:612397

  • Received: 10 November 2007
  • Accepted: 14 April 2008
  • Published:


We detect key information of high-dimensional microarray profiles based on wavelet analysis and genetic algorithm. Firstly, wavelet transform is employed to extract approximation coefficients at 2nd level, which remove noise and reduce dimensionality. Genetic algorithm (GA) is performed to select the optimized features. Experiments are performed on four datasets, and experimental results prove that approximation coefficients are efficient way to characterize the microarray data. Furthermore, in order to detect the key genes in the classification of cancer tissue, we reconstruct the approximation part of gene profiles based on orthogonal approximation coefficients. The significant genes are selected based on reconstructed approximation information using genetic algorithm. Experiments prove that good performance of classification is achieved based on the selected key genes.


  • Genetic Algorithm
  • Cancer Tissue
  • Microarray Data
  • Significant Gene
  • Quantum Information

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Authors’ Affiliations

School of Computer Science and Information Technology, Shandong Institute of Light Industry, Jinan, Shandong, 250353, China


© Yihui Liu. 2008

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.