Calling on a million minds for community annotation in WikiProteins
2008

WikiProteins: Community Annotation for Biomedical Concepts

publication Evidence: moderate

Author Information

Author(s): Mons Barend, Ashburner Michael, Chichester Christine, van Mulligen Erik, Weeber Marc, den Dunnen Johan, van Ommen Gert-Jan, Musen Mark, Cockerill Matthew, Hermjakob Henning, Mons Albert, Packer Abel, Pacheco Roberto, Lewis Suzanna, Berkeley Alfred, Melton William, Barris Nickolas, Wales Jimmy, Meijssen Gerard, Moeller Erik, Roes Peter Jan, Borner Katy, Bairoch Amos

Hypothesis

A combination of text mining and community annotation can enhance the curation of biomedical literature.

Conclusion

WikiProteins allows for collaborative knowledge discovery by enabling community annotation of biomedical concepts.

Supporting Evidence

  • WikiProteins integrates data from various authoritative biomedical databases.
  • The system allows users to edit and annotate concepts collaboratively.
  • Community contributions can enhance the accuracy of biomedical information.

Takeaway

WikiProteins is like a big online book where many people can help write and correct information about biology, making it easier to find facts about genes and proteins.

Methodology

The study describes the development of WikiProteins, a web-based system for community annotation and knowledge discovery, integrating text mining and user contributions.

Potential Biases

Potential biases may arise from the varying expertise of contributors and the reliance on community edits.

Limitations

The system relies on community participation, which may vary in quality and consistency.

Digital Object Identifier (DOI)

10.1186/gb-2008-9-5-r89

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