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Related Experiment Videos

From global expression data to gene networks.

D Thieffry1

  • 1Unité de Bioinformatique, IBMM-ULB, 12 rue des Professeurs Jeener et Brachet, B-6041 Gosselies, Belgium. denis@dbm.ulb.ac.be

Bioessays : News and Reviews in Molecular, Cellular and Developmental Biology
|October 12, 1999
PubMed
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Researchers used microarrays to analyze gene transcription. They combined clustering and alignment software to find DNA motifs in yeast genes with similar expression patterns, advancing genomic network understanding.

Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Microarrays enable parallel monitoring of thousands of gene transcriptions.
  • Functional genomics relies on techniques like microarrays for large-scale gene expression analysis.

Purpose of the Study:

  • To identify DNA motifs within sets of yeast genes exhibiting similar transcription profiles during mitosis.
  • To systematically characterize the regulatory structure of genomic networks.

Main Methods:

  • Utilized a clustering method to group genes with similar transcription profiles.
  • Employed local alignment software to identify DNA motifs in these gene sets.

Main Results:

  • Successfully identified known transcriptional binding sites.

Related Experiment Videos

  • Discovered new putative DNA motifs.
  • Advanced the systematic characterization of genomic regulatory networks.

    • Conclusions:

    • The combined approach of clustering and local alignment is effective for motif discovery in yeast.
    • This methodology contributes significantly to understanding gene regulation and genomic networks.