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Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

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The Merck Gene Index browser: an extensible data integration system for gene finding, gene characterization and EST

B A Eckman¹, J S Aaronson, J A Borkowski

¹Department of Bioinformatics, Merck Research Laboratories, West Point, PA, USA. barbara_eckman@sbphrd.com

Bioinformatics (Oxford, England)

|April 1, 1998

Summary

The Merck Gene Index browser organizes expressed sequence tag (EST) data into gene classes, enabling scientists to mine this information alongside genomic data for enhanced biological insights.

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Area of Science:

Bioinformatics
Genomics
Computational Biology

Background:

Vast amounts of expressed sequence tag (EST) data require organization into gene classes.
Effective mining of gene class data necessitates integration with related genomic information.

Purpose of the Study:

To present the Merck Gene Index (MGI) browser, a World Wide Web-based system.
To enable scientists to mine the MGI and related genomic data.

Main Methods:

Developed an easily extensible, web-based system.
Integrated diverse data sources (LENS, dbEST, WashU, Entrez, UniGene) using a federation of relational databases, a data warehouse, and hypertext links.
Utilized the Bioapps server for flatfile sequence data access and the Bioinformatics Data Integration Toolkit (B-DIT) for data retrieval and formatting.

Main Results:

The MGI browser provides a non-redundant set of clones and sequences representing distinct genes from EST data.
Integrated data includes cDNA clone, EST, protein similarity, sequence chromatograms, Entrez, Medline, and UniGene cluster information.
The system supports generic sequence analysis applications.

Conclusions:

The MGI browser facilitates the organization and mining of EST and genomic data.
This integrated system enhances the utility of large-scale sequence data for scientific research.