Clustering Causal Relationships in Genes Expression Data

  • Sergio Pozzi
  • Italo Zoppis
  • Giancarlo Mauri
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3931)


In this paper we apply a strategy to cluster gene expression data. In order to identify causal relationships among genes, we apply a pruning procedure [Chen et al., 1999] on the basis of the statistical cross-correlation function between couples of genes’ time series. Finally we try to isolate genes’ patterns in groups with positive causal relationships within groups and negative causal relation among groups. With this aim, we use a simple recursive clustering algorithm [Ailon et al., 2005].


Gene Expression Data Boolean Variable Correlation Cluster Cross Correlation Matrix Cluster Gene Expression Data 
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 2006

Authors and Affiliations

  • Sergio Pozzi
    • 1
  • Italo Zoppis
    • 1
  • Giancarlo Mauri
    • 1
  1. 1.DISCoUniv. Milano-BicoccaMilanoItaly

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