Title |
DGIdb: mining the druggable genome
|
---|---|
Published in |
Nature Methods, October 2013
|
DOI | 10.1038/nmeth.2689 |
Pubmed ID | |
Authors |
Malachi Griffith, Obi L Griffith, Adam C Coffman, James V Weible, Josh F McMichael, Nicholas C Spies, James Koval, Indraniel Das, Matthew B Callaway, James M Eldred, Christopher A Miller, Janakiraman Subramanian, Ramaswamy Govindan, Runjun D Kumar, Ron Bose, Li Ding, Jason R Walker, David E Larson, David J Dooling, Scott M Smith, Timothy J Ley, Elaine R Mardis, Richard K Wilson |
Abstract |
The Drug-Gene Interaction database (DGIdb) mines existing resources that generate hypotheses about how mutated genes might be targeted therapeutically or prioritized for drug development. It provides an interface for searching lists of genes against a compendium of drug-gene interactions and potentially 'druggable' genes. DGIdb can be accessed at http://dgidb.org/. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 15 | 38% |
Canada | 3 | 8% |
Spain | 3 | 8% |
United Kingdom | 2 | 5% |
Belgium | 2 | 5% |
Australia | 1 | 3% |
Germany | 1 | 3% |
Netherlands | 1 | 3% |
Montenegro | 1 | 3% |
Other | 0 | 0% |
Unknown | 10 | 26% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 25 | 64% |
Members of the public | 12 | 31% |
Practitioners (doctors, other healthcare professionals) | 1 | 3% |
Science communicators (journalists, bloggers, editors) | 1 | 3% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 17 | 3% |
Germany | 4 | <1% |
Spain | 4 | <1% |
United Kingdom | 4 | <1% |
Brazil | 3 | <1% |
Japan | 2 | <1% |
Korea, Republic of | 2 | <1% |
Argentina | 1 | <1% |
Denmark | 1 | <1% |
Other | 5 | <1% |
Unknown | 498 | 92% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 142 | 26% |
Student > Ph. D. Student | 133 | 25% |
Student > Master | 44 | 8% |
Student > Bachelor | 43 | 8% |
Other | 27 | 5% |
Other | 87 | 16% |
Unknown | 65 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 175 | 32% |
Biochemistry, Genetics and Molecular Biology | 113 | 21% |
Medicine and Dentistry | 47 | 9% |
Computer Science | 32 | 6% |
Chemistry | 22 | 4% |
Other | 69 | 13% |
Unknown | 83 | 15% |