Title |
BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models
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Published in |
BMC Systems Biology, June 2010
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DOI | 10.1186/1752-0509-4-92 |
Pubmed ID | |
Authors |
Chen Li, Marco Donizelli, Nicolas Rodriguez, Harish Dharuri, Lukas Endler, Vijayalakshmi Chelliah, Lu Li, Enuo He, Arnaud Henry, Melanie I Stefan, Jacky L Snoep, Michael Hucka, Nicolas Le Novère, Camille Laibe |
Abstract |
Quantitative models of biochemical and cellular systems are used to answer a variety of questions in the biological sciences. The number of published quantitative models is growing steadily thanks to increasing interest in the use of models as well as the development of improved software systems and the availability of better, cheaper computer hardware. To maximise the benefits of this growing body of models, the field needs centralised model repositories that will encourage, facilitate and promote model dissemination and reuse. Ideally, the models stored in these repositories should be extensively tested and encoded in community-supported and standardised formats. In addition, the models and their components should be cross-referenced with other resources in order to allow their unambiguous identification. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 13 | 4% |
United Kingdom | 11 | 3% |
Germany | 9 | 2% |
Spain | 3 | <1% |
Austria | 2 | <1% |
Portugal | 2 | <1% |
Russia | 2 | <1% |
Mexico | 2 | <1% |
Australia | 1 | <1% |
Other | 8 | 2% |
Unknown | 310 | 85% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 102 | 28% |
Student > Ph. D. Student | 93 | 26% |
Student > Bachelor | 28 | 8% |
Student > Master | 25 | 7% |
Professor | 18 | 5% |
Other | 58 | 16% |
Unknown | 39 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 137 | 38% |
Computer Science | 61 | 17% |
Biochemistry, Genetics and Molecular Biology | 47 | 13% |
Engineering | 19 | 5% |
Medicine and Dentistry | 14 | 4% |
Other | 40 | 11% |
Unknown | 45 | 12% |