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Related Experiment Videos

Code generation through annotation of macromolecular structure data

J Biggs1, C Pu, P Bourne

  • 1Department of Computer Science and Engineering, Oregon Graduate Institute of Science & Technology, Portland 97291-1000, USA. biggs@cse.ogi.edu

Proceedings. International Conference on Intelligent Systems for Molecular Biology
|January 1, 1997
PubMed
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Maintaining software for evolving data annotation schemes like macromolecular Crystallographic Information File (mmCIF) is challenging. A new domain-specific language (DSL) simplifies mmCIF and Protein Data Bank (PDB) annotation code conversion.

Area of Science:

  • Structural Biology
  • Bioinformatics
  • Computational Biology

Background:

  • Software maintenance for evolving data annotation schemes is costly and time-consuming.
  • Limited software adoption hinders the widespread use of annotation schemes.
  • Macromolecular Crystallographic Information File (mmCIF) is a structured annotation for crystallographic data.

Purpose of the Study:

  • To develop a generalized solution for maintaining software associated with evolving data annotation schemes.
  • To address the challenge of keeping conversion code between mmCIF and Protein Data Bank (PDB) annotations current.
  • To ensure consistent data conversion by integrating it into a global dictionary.

Main Methods:

  • A domain-specific language (DSL) was integrated into the mmCIF dictionary.

Related Experiment Videos

  • The DSL utilizes specific mapping modules for data item categories.
  • A code generator creates executable conversion tools from updated mapping modules.

    • Main Results:

    • The DSL simplifies the process of updating mappings between mmCIF and PDB annotations.
    • Code generation ensures that conversion tools remain current with annotation scheme changes.
    • The approach allows individuals with domain expertise but limited programming skills to manage code updates.

    Conclusions:

    • The developed DSL and code generator provide an efficient and maintainable solution for evolving annotation schemes.
    • This method standardizes data conversion, preventing varied interpretations across research groups.
    • The approach is generalizable to other molecular biology data annotation schemes.