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Identifying Characteristic Genes Based on Robust Principal Component Analysis

  • Chun-Hou Zheng
  • Jin-Xing Liu
  • Jian-Xun Mi
  • Yong Xu
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 304)

Abstract

In this paper, based on robust PCA, a novel method of characteristic genes identification is proposed. In our method, the differentially expressed genes and non-differentially expressed genes are treated as perturbation signals S 0 and low-rank matrix A 0, respectively, which can be recovered from the gene expression data using robust PCA. The scheme to identify the characteristic genes is as following. Firstly, the matrix S 0 of perturbation signals is discovered from gene expression data matrix D by using robust PCA. Secondly, the characteristic genes are selected according to matrix S 0. Finally, the characteristic genes are checked by the tool of Gene Ontology. The experimental results show that our method is efficient and effective.

Keywords

robust PCA gene identification gene expression data 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Chun-Hou Zheng
    • 1
  • Jin-Xing Liu
    • 2
    • 3
  • Jian-Xun Mi
    • 2
  • Yong Xu
    • 2
  1. 1.College of Electrical Engineering and AutomationAnhui UniversityHefeiChina
  2. 2.Bio-Computing Research Center, Shenzhen Graduate SchoolHarbin Institute of TechnologyShenzhenChina
  3. 3.College of Information and Communication TechnologyQufu Normal UniversityRizhaoChina

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