Title |
Mining the Gene Wiki for functional genomic knowledge
|
---|---|
Published in |
BMC Genomics, December 2011
|
DOI | 10.1186/1471-2164-12-603 |
Pubmed ID | |
Authors |
Benjamin M Good, Douglas G Howe, Simon M Lin, Warren A Kibbe, Andrew I Su |
Abstract |
Ontology-based gene annotations are important tools for organizing and analyzing genome-scale biological data. Collecting these annotations is a valuable but costly endeavor. The Gene Wiki makes use of Wikipedia as a low-cost, mass-collaborative platform for assembling text-based gene annotations. The Gene Wiki is comprised of more than 10,000 review articles, each describing one human gene. The goal of this study is to define and assess a computational strategy for translating the text of Gene Wiki articles into ontology-based gene annotations. We specifically explore the generation of structured annotations using the Gene Ontology and the Human Disease Ontology. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
China | 1 | 14% |
Canada | 1 | 14% |
Sweden | 1 | 14% |
United Kingdom | 1 | 14% |
Netherlands | 1 | 14% |
Unknown | 2 | 29% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 4 | 57% |
Members of the public | 3 | 43% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 5 | 11% |
Sweden | 1 | 2% |
Brazil | 1 | 2% |
Unknown | 37 | 84% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 12 | 27% |
Student > Ph. D. Student | 7 | 16% |
Professor > Associate Professor | 6 | 14% |
Other | 4 | 9% |
Student > Master | 3 | 7% |
Other | 6 | 14% |
Unknown | 6 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 17 | 39% |
Computer Science | 7 | 16% |
Medicine and Dentistry | 5 | 11% |
Engineering | 3 | 7% |
Chemistry | 1 | 2% |
Other | 1 | 2% |
Unknown | 10 | 23% |