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Related Experiment Videos

CLICK and EXPANDER: a system for clustering and visualizing gene expression data.

Roded Sharan1, Adi Maron-Katz, Ron Shamir

  • 1International Computer Science Institute, 1947 Center St., Suite 600, Berkeley, CA 94704-1198, USA. roded@icsi.berkeley.edu

Bioinformatics (Oxford, England)
|September 27, 2003
PubMed
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A new clustering algorithm, CLICK, enhances gene expression analysis by identifying gene groups and outperforming existing methods. It aids in discovering regulatory motifs and classifying diseases from expression profiles.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Microarrays are crucial for biological research, enabling functional annotation, tissue classification, and genetic network inference.
  • Analyzing gene expression data requires identifying genes with similar expression patterns, a task addressed by gene clustering algorithms.

Purpose of the Study:

  • To introduce a novel clustering algorithm, CLICK, for gene expression analysis.
  • To demonstrate CLICK's effectiveness in identifying gene groups, regulatory motifs, and classifying diseases.

Main Methods:

  • CLICK utilizes graph-theoretic and statistical techniques to find tight groups (kernels) of similar elements.
  • Heuristic procedures are employed to expand these kernels into complete clusters.
  • The EXPANDER tool, a Java-based graphical interface, incorporates CLICK and other clustering algorithms for analysis and visualization.

Related Experiment Videos

Main Results:

  • CLICK outperformed existing algorithms across various gene expression datasets based on common figures of merit.
  • The algorithm successfully identified common regulatory motifs in co-regulated genes.
  • CLICK accurately classified tissue samples into disease types using their expression profiles.

Conclusions:

  • CLICK offers a superior approach to gene clustering in expression data analysis.
  • The algorithm has broad applications, including motif discovery and disease classification.
  • The EXPANDER tool provides a user-friendly platform for leveraging CLICK and other clustering methods.