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Compression of protein sequence databases

V B Strelets1, H A Lim

  • 1Computational Genetics and Biophysics, Supercomputer Computations Research Institute, Florida State University, Tallahassee 32306-4052, USA.

Computer Applications in the Biosciences : CABIOS
|October 1, 1995
PubMed
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We developed a novel algorithm to compress the Protein Information Resource (PIR) database, creating a compact databank for researchers with limited storage. This tool offers fast, direct access to sequence data and supports standard queries, even on personal computers.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Database Management

Background:

  • Researchers often face storage limitations when working with large biological sequence databases like PIR.
  • Existing methods for accessing PIR data may require significant storage or network access, hindering individual researchers and developers.

Purpose of the Study:

  • To develop a space-efficient algorithm for compressing the PIR database.
  • To create a C-based interface for fast, direct access to compressed PIR data without extensive decompression.
  • To enable standalone use of PIR data on personal computers and UNIX systems.

Main Methods:

  • An alignment-based algorithm was developed for compressing protein sequences.
  • The PIR database was restructured into separate file sets for modularity.

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  • A C language interface was implemented to support standard PIR queries and direct programmatic access.
  • Main Results:

    • A compact PIR databank, SAGITTARIUS PIR, was created, significantly outperforming ZIP compression for protein sequences.
    • The C interface allows direct data retrieval from PIR without network dependency or full decompression.
    • The system supports standard PIR queries and offers additional features like homology searches on PC-compatibles.

    Conclusions:

    • The SAGITTARIUS PIR package provides an efficient solution for researchers needing to access PIR data with limited storage.
    • The developed compression algorithm and access interface enhance the usability of biological sequence databases on diverse computing platforms.
    • This tool empowers individual researchers and software developers by offering flexible and fast access to critical sequence information.