It has been evident that the annotation of the human genome is an important scientific and academic enterprise that needs large resources.
Dr. Andrew I. Su and colleagues (yes, he is the same "Su AI" from the highly cited paper (3)) identified a scale-free network structure in the number of annotations for human genes (2). This type of structure (having a power law distribution) means that a large number of genes have few annotations while few genes have a large number of annotations (different from a normal distribution). It could be related in part to a preference of scientists to focus their interest in well-studied genes. As an example, around 19.000 entries (49 percent) in Entrez Gene database have zero references in PubMed and less than 4 percent of recent PubMed entries have links to Entrez Gene (1).
In order to explore innovative approaches for gene annotation, Andrew and colleagues created around 8.000 "stubs" (using automatic retrieval of info from several systematic databases) in Wikipedia about human genes to foster community-based gene annotation (4).
A paper in press in Nucleic Acid Research (1) describes the advances in the Gene Wiki in recent months. Some statistics show its broad use and rapid growth in a short time: 9.678 Gene Wiki pages with around 3.000.000 views/month and close to 1.900 contributors. It has benefited from the open resources and experience that are available inside the Wikipedia community.
In addition to being a successful (and complementary) approach for community-based annotation of human genes, the Gene Wiki initiative is a useful basic educational resource for students and scientists in molecular life sciences. It is also a good platform to bring freely available and accurate basic scientific information about human genes to the general public at large.
You are invited to contribute to the entries about your favorite genes.
"We are partnering with organizations that do traditional manual curation of gene function so that the Gene Wiki can be used as another resource in their workflows. We are also looking to grow in acceptance and usage among scientists."
Andrew I. Su, PhD
Computational Biology Group, Genomics Institute of the Novartis Research Foundation, San Diego, USA
(1) Huss JW 3rd, Lindenbaum P, Martone M, Roberts D, Pizarro A, Valafar F, Hogenesch JB, Su AI. The Gene Wiki: community intelligence applied to human gene annotation. Nucleic Acids Res. 2009 Sep 15. (Free full text)
(2) Su AI, Hogenesch JB. Power-law-like distributions in biomedical publications and research funding. Genome Biol. 2007;8(4):404. (Free full text)
(3) Su AI, Wiltshire T, Batalov S, Lapp H, Ching KA, Block D, Zhang J, Soden R, Hayakawa M, Kreiman G, Cooke MP, Walker JR, Hogenesch JB. A gene atlas of the mouse and human protein-encoding transcriptomes. Proc Natl Acad Sci U S A. 2004 Apr 20;101(16):6062-7. (Free full text)
(4) Huss JW 3rd, Orozco C, Goodale J, Wu C, Batalov S, Vickers TJ, Valafar F, Su AI. A gene wiki for community annotation of gene function. PLoS Biol. 2008 Jul 8;6(7):e175. (Free full text)
Diego Forero, MD
Message posted by: Diego Forero