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Related Experiment Videos

Searching the expressed sequence tag (EST) databases: panning for genes.

C V Jongeneel1

  • 1Office of Information Technology, Ludwig Institute for Cancer Research and Swiss Institute of Bioinformatics, chemin des Boveresses 155, CH-1066 Epalinges, Switzerland. Victor.Jongeneel@licr.org

Briefings in Bioinformatics
|July 27, 2001
PubMed
Summary

Expressed sequence tag (EST) databases offer a vast resource for discovering novel protein sequences. This review details methods and tools for effectively mining these valuable, yet often unorganized, biological datasets.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Genomes contain coding and non-coding regions, with the transcriptome representing expressed genes.
  • Expressed Sequence Tag (EST) databases are a major repository of transcriptome data for numerous species.
  • EST data is abundant but often unorganized, unannotated, and of low quality.

Purpose of the Study:

  • To review the characteristics of EST data.
  • To present methods for identifying novel protein sequences within EST databases.
  • To document resources for EST data analysis.

Main Methods:

  • Review of EST database characteristics.
  • Exploration of computational methods for novel protein sequence discovery.
  • Compilation of relevant databases, software, and web resources.

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Main Results:

  • EST databases are a primary source for new coding sequences.
  • Various methods exist for processing and analyzing raw EST data.
  • Numerous online and local tools facilitate EST data mining.

Conclusions:

  • EST databases are crucial for discovering new protein-coding sequences.
  • Effective mining requires understanding EST data characteristics and employing appropriate bioinformatics tools.
  • Accessible resources aid biologists in leveraging EST data for research.