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Related Experiment Videos

PIR-ALN: a database of protein sequence alignments.

G Y Srinivasarao1, L S Yeh, C R Marzec

  • 1Protein Information Resource (PIR), National Biomedical Research Foundation, 3900 Reservoir Road NW, Washington, DC 20007, USA. Geetha@nbrf.georgetown.edu

Bioinformatics (Oxford, England)
|June 15, 1999
PubMed
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The Protein Information Resource (PIR) alignment database (PIR-ALN) Release 22.0 offers 3806 curated alignments for protein sequence analysis. This resource aids in classifying sequences, identifying conserved regions, and defining homology domains.

Area of Science:

  • Bioinformatics
  • Structural Biology
  • Computational Biology

Background:

  • The Protein Information Resource (PIR) curates annotated alignments to represent sequence interrelationships within the PIR-International Protein Sequence Database.
  • Standardizing protein nomenclature, features, and keywords across families and superfamilies is crucial for biological classification.
  • These alignments assist in identifying conserved regions and defining novel homology domains.

Purpose of the Study:

  • To provide a comprehensive dataset of curated protein sequence alignments for various bioinformatics applications.
  • To facilitate the standardization and dissemination of protein annotation through homology.
  • To support the understanding of multidomain protein architecture.

Main Methods:

Related Experiment Videos

  • The PIR-ALN database (Release 22.0) comprises 3806 curated alignments.
  • Includes 1303 superfamily, 2131 family, and 372 homology domain alignments.
  • Utilizes the ATLAS information retrieval system for browsing and querying alignments.

    • Main Results:

    • PIR-ALN Release 22.0 contains 3806 alignments, suitable for developing patterns, testing profiles, and training models like Hidden Markov Models (HMMs).
    • Identifies 529 alignments for developing patterns not found in PROSITE, Blocks, PRINTS, and Pfam.
    • Supports annotation standardization for new protein members via homology.

    Conclusions:

    • The PIR-ALN database serves as a valuable resource for protein sequence analysis and annotation.
    • Facilitates the discovery of conserved regions and the definition of new homology domains.
    • Enables a deeper understanding of protein modular architecture and evolutionary relationships.