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SORTEZ: a relational translator for NCBI's ASN.1 database

K W Hart1, D B Searls, G C Overton

  • 1Department of Genetics, University of Pennsylvania School of Medicine, Philadelphia 19104-6145.

Computer Applications in the Biosciences : CABIOS
|July 1, 1994
PubMed
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The National Center for Biotechnology Information (NCBI) database, modeled in ASN.1, can now be queried using SQL. The SORTEZ package transforms ASN.1 data into a relational model for easier access.

Area of Science:

  • Bioinformatics
  • Database Management
  • Computational Biology

Background:

  • The National Center for Biotechnology Information (NCBI) provides extensive biological sequence and literature databases.
  • NCBI data is structured using Abstract Syntax Notation 1 (ASN.1), which is not optimized for direct database querying.
  • Existing retrieval systems like ENTREZ offer limited ad hoc query capabilities for the ASN.1 data model.

Purpose of the Study:

  • To develop a method for accessing NCBI's ASN.1 structured data using standard relational database query languages.
  • To address the lack of an ad hoc query language for the NCBI's ASN.1 data model.
  • To explore the challenges and solutions in transforming complex nested data structures into relational databases.

Main Methods:

  • Developed the SORTEZ software package to transform ASN.1 data into a relational data model.

Related Experiment Videos

  • Migrated the transformed relational data into a Sybase relational database management system.
  • Utilized SQL (Structured Query Language) for data retrieval from the relational database.

    • Main Results:

    • Successfully transformed NCBI's ASN.1 data into a relational model compatible with Sybase.
    • Enabled general-purpose data access to NCBI databases via SQL queries.
    • Demonstrated that ASN.1 to relational data model transformation can be largely automated.

    Conclusions:

    • The SORTEZ package provides a viable solution for querying NCBI data using SQL.
    • Schema transformation and data conversion stages require significant domain expertise and tool support.
    • This work highlights the practical challenges and considerations in database transformation processes.