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Efficiently finding regulatory elements using correlation with gene expression.

Hideo Bannai1, Shunsuke Inenaga, Ayumi Shinohara

  • 1Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo 108-8639, Japan. bannai@ims.u.tokyo.ac.jp

Journal of Bioinformatics and Computational Biology
|August 7, 2004
PubMed
Summary
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We developed an efficient algorithm to find DNA motifs correlated with gene expression. This method uses a generalized suffix tree to identify regulatory elements in upstream gene sequences, significantly improving motif discovery.

Area of Science:

  • Computational Biology
  • Genomics
  • Bioinformatics

Background:

  • Identifying regulatory elements in DNA is crucial for understanding gene regulation.
  • Gene expression data from microarrays provides a valuable resource for inferring regulatory mechanisms.

Purpose of the Study:

  • To develop an efficient algorithm for detecting putative regulatory elements in upstream DNA sequences.
  • To correlate DNA motif patterns with gene expression levels.

Main Methods:

  • Utilized a generalized suffix tree for efficient pattern searching.
  • Developed an algorithm with linear time complexity relative to the total length of upstream sequences.
  • Applied the algorithm to publicly available microarray gene expression data.

Related Experiment Videos

Main Results:

  • Successfully identified biologically significant motifs, including previously reported ones.
  • Demonstrated the algorithm's ability to find optimal patterns correlating with gene expression.
  • Achieved efficient detection of regulatory elements.

Conclusions:

  • The developed algorithm is efficient and effective for discovering regulatory motifs.
  • The method has practical applications where computational efficiency is critical.
  • Potential extensions to the algorithm can further enhance its capabilities.