Crowdsourcing biocuration: The Community Assessment of Community Annotation with Ontologies (CACAO)

Area of Science:

• Bioinformatics
• Genomics
• Scientific Curation

Background:

• Gene Ontology (GO) provides valuable gene function data curated from scientific literature.
• The rapid growth of scientific literature challenges manual biocuration efforts.
• Existing curation methods struggle to keep pace with the expanding volume of biological data.

Purpose of the Study:

• To describe a crowdsourcing approach using undergraduates to expand biocuration for the Gene Ontology.
• To increase the number of high-quality, literature-based gene function annotations.
• To enrich the coverage of gene function in underrepresented organisms within GO.

Main Methods:

• Utilizing the Gene Ontology Normal Usage Tracking System (GONUTS) wiki framework.
• Implementing a crowdsourcing model involving undergraduate students in biocuration.
• Organizing an intercollegiate competition, Community Assessment of Community Annotation with Ontologies (CACAO), judged by expert biocurators.

Main Results:

• Generated nearly 5,000 literature-based annotations through the CACAO competition.
• Added annotations for organisms not well-represented in the Gene Ontology.
• Influenced changes in the ontology not traditionally covered by professional biocurators over a 10-year period.

Conclusions:

• Crowdsourcing with undergraduates is a scalable and effective model for expanding biocuration.
• This approach enhances the Gene Ontology database and promotes scientific discovery.
• It offers undergraduates valuable experience in scientific literature analysis and skill development.