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Shared resources, shared costs--leveraging biocuration resources.

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Summary
This summary is machine-generated.

Manual curation of biomedical data is valuable despite costs. Sharing infrastructure and development efforts among databases offers significant cost savings and ensures data persistence.

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Area of Science:

  • Biomedical Informatics
  • Data Curation
  • Bioinformatics Resource Management

Background:

  • Manual curation of biomedical data is essential but costly.
  • Automated annotation and text-mining present less expensive alternatives.
  • Efficient data management is crucial for scientific advancement.

Purpose of the Study:

  • To argue for the value of manual curation in biomedical resources.
  • To explore cost-saving strategies for databases through shared development.
  • To review successful models of shared curation efforts.

Main Methods:

  • Comparative analysis of manual curation versus automated methods.
  • Discussion of infrastructure and tool development sharing.
  • Case studies of the Gene Ontology (GO) annotation and IntAct molecular interaction database.

Main Results:

  • Manual curation provides high-quality, reliable data essential for research.
  • Shared infrastructure and development reduce costs and prevent redundant efforts.
  • Collaborative models ensure long-term data persistence and accessibility.

Conclusions:

  • Manual curation remains a vital approach for high-quality biomedical data.
  • Database collaboration through shared resources is a cost-effective and sustainable model.
  • Adoption of shared curation efforts enhances data integrity and accessibility for the scientific community.