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Model-based identification of cis-acting elements from microarray data.

Yunlong Liu1, Milton W Taylor, Howard J Edenberg

  • 1Department of Biochemistry and Molecular Biology and Center for Medical Genomics, Indiana University School of Medicine, 635 Barnhill Drive MS 4063, Indianapolis, IN 46202, USA.

Genomics
|May 24, 2006
PubMed
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MotifModeler computationally identifies cis-acting elements (CAE) regulating gene expression using global expression data. This method successfully predicted motifs involved in interferon action, advancing computational biology.

Area of Science:

  • Computational biology
  • Genomics
  • Bioinformatics

Background:

  • Identifying transcriptional regulatory motifs is a significant challenge.
  • Understanding gene regulation is crucial for biological research.

Purpose of the Study:

  • To introduce MotifModeler, a novel computational approach.
  • To identify cis-acting elements (CAE) and their regulatory effects.
  • To analyze gene expression data for motif discovery.

Main Methods:

  • A model-based procedure, MotifModeler, was developed.
  • Global gene expression data was utilized.
  • Random subsets of motifs were tested against a combinatorial model.
  • Position-specific scoring matrices were used for comparison with TRANSFAC.

Related Experiment Videos

Main Results:

  • MotifModeler identified 16 stimulatory and 4 inhibitory 6-bp motifs.
  • Predicted CAE showed matches to known sites involved in interferon action.
  • The method was validated using microarray data from interferon-alpha treated monocytes.

Conclusions:

  • MotifModeler effectively identifies functional cis-acting elements.
  • The approach has the potential to advance the study of gene regulation.
  • This computational tool aids in understanding complex biological processes.