Strategies for community-sourced biocuration in bioinformatics: a case study on MIBiG 4.0

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics
• Natural Product Discovery

Background:

• Biocuration transforms raw molecular sequence data into standardized, machine-readable resources essential for bioinformatics.
• Professional biocuration is resource-intensive and often confined to institutional settings.
• Community-driven approaches offer a scalable and resilient alternative for large-scale dataset annotation.

Purpose of the Study:

• To present and evaluate a model for community-powered biocuration using the Minimum Information about a Biosynthetic Gene Cluster (MIBiG) repository.
• To assess the impact of community efforts on repository expansion and usability for downstream applications.

Main Methods:

• Implementation of a framework for metadata capture, annotation validation, and contributor coordination for the MIBiG 4.0 initiative.
• Recruitment of 267 scientists from 178 institutions across 33 countries, contributing an estimated 4000 hours of work.
• Leveraging community contributions to expand and enhance the MIBiG repository.

Main Results:

• The MIBiG repository was expanded by 22% through community-driven curation efforts.
• Enhanced usability of the MIBiG repository for comparative genomic analyses, natural product discovery, and machine learning applications.
• Demonstrated the effectiveness of a community-powered model in mobilizing large-scale scientific data annotation.

Conclusions:

• Community-powered biocuration is a viable and effective model for expanding and enhancing specialized bioinformatics resources like MIBiG.
• This approach enhances data usability for critical research areas, including comparative genomics and drug discovery.
• Provides actionable strategies for sustaining curated bioinformatics resources through collaborative scientific engagement.