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Multiclass Microarray Gene Expression Analysis Based on Mutual Dependency Models

  • Girija Chetty
  • Madhu Chetty
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5780)

Abstract

In this paper a novel feature selection technique based on mutual dependency modelling between genes is proposed for multiclass microarray gene expression classification. Several studies on analysis of gene expression data has shown that the genes (whether or not they belong to the same gene group) get co-expressed via a variety of pathways. Further, a gene may participate in multiple pathways that may or may not be co-active for all samples. It is therefore biologically meaningful to simultaneously divide genes into functional groups and samples into co-active categories. This can be done by modeling gene profiles for multiclass microarray gene data sets based on mutual dependency models, which model complex gene interactions. Most of the current works in multiclass microarray gene expression studies are based on statistical models with little or no consideration of gene interactions. This has led to lack of robustness and overly optimistic estimates of accuracy and noise reduction. In this paper, we propose multivariate analysis techniques which model the mutual dependency between the features and take into account complex interactions for extracting a subset of genes. The two techniques, the cross modal factor analysis (CFA) and canonical correlation analysis(CCA) show a significant reduction in dimensionality and class-prediction error, and improvement in classification accuracy for multiclass microarray gene expression datasets.

Keywords

Classification Accuracy Canonical Correlation Analysis Mutual Dependency Class Accuracy Feature Selection Technique 
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 2009

Authors and Affiliations

  • Girija Chetty
    • 1
  • Madhu Chetty
    • 2
  1. 1.Faculty of Information Sciences and EngineeringUniversity of CanberraAustralia
  2. 2.Faculty of Information TechnologyMonash UniversityVictoriaAustralia

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