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Integrated databases and computer systems for studying eukaryotic gene expression.

N A Kolchanov1, M P Ponomarenko, A S Frolov

  • 1Institute of Cytology & Genetics, Siberian Branch of the Russian Academy of Sciences, Prosp. Lavrentieva 10, Novosibirsk 630090, Russia. kol@bionet.nsc.ru

Bioinformatics (Oxford, England)
|September 17, 1999
PubMed
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This summary is machine-generated.

The GeneExpress system integrates databases and software for analyzing gene expression regulation. It aids in discovering knowledge for genomic sequence analysis and understanding gene networks.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • The exponential growth of gene expression data necessitates advanced computational systems.
  • Automated knowledge discovery is crucial for analyzing regulatory genomic sequences.

Purpose of the Study:

  • To develop a WWW-oriented system for maximal integration of information and software resources for gene expression regulation.
  • To facilitate navigation and analysis of complex gene regulatory data.

Main Methods:

  • Development of the GeneExpress system with integrated modules.
  • Utilizing databases for transcription regulation, site activity prediction, and gene networks.
  • Incorporating tools for DNA site recognition and mRNA translation efficiency prediction.

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Main Results:

  • The GeneExpress system includes modules for Transcription Regulation (TRRD), Site Activity Prediction (ACTIVITY), Site Recognition (B-DNA-VIDEO, ConsFrec, TFBSR), Gene Networks (GeneNet), and mRNA Translation (Leader mRNA).
  • These modules provide visualization, prediction, and analysis capabilities for regulatory genomic sequences.
  • The system facilitates the study of structure-function organization in regulatory elements and proteins.

Conclusions:

  • GeneExpress offers a comprehensive platform for exploring gene expression regulation.
  • The integrated approach enhances the analysis of genomic regulatory data.
  • The system supports research into gene networks and protein interactions.