Title |
Promoting Coordinated Development of Community-Based Information Standards for Modeling in Biology: The COMBINE Initiative
|
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Published in |
Frontiers in Bioengineering and Biotechnology, February 2015
|
DOI | 10.3389/fbioe.2015.00019 |
Pubmed ID | |
Authors |
Michael Hucka, David P. Nickerson, Gary D. Bader, Frank T. Bergmann, Jonathan Cooper, Emek Demir, Alan Garny, Martin Golebiewski, Chris J. Myers, Falk Schreiber, Dagmar Waltemath, Nicolas Le Novère |
Abstract |
The Computational Modeling in Biology Network (COMBINE) is a consortium of groups involved in the development of open community standards and formats used in computational modeling in biology. COMBINE's aim is to act as a coordinator, facilitator, and resource for different standardization efforts whose domains of use cover related areas of the computational biology space. In this perspective article, we summarize COMBINE, its general organization, and the community standards and other efforts involved in it. Our goals are to help guide readers toward standards that may be suitable for their research activities, as well as to direct interested readers to relevant communities where they can best expect to receive assistance in how to develop interoperable computational models. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 17% |
Germany | 3 | 17% |
United Kingdom | 2 | 11% |
Japan | 1 | 6% |
Sweden | 1 | 6% |
New Zealand | 1 | 6% |
Switzerland | 1 | 6% |
Unknown | 6 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 12 | 67% |
Scientists | 5 | 28% |
Practitioners (doctors, other healthcare professionals) | 1 | 6% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 4% |
United States | 2 | 4% |
Turkey | 1 | 2% |
Portugal | 1 | 2% |
Unknown | 50 | 89% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 17 | 30% |
Student > Ph. D. Student | 10 | 18% |
Professor | 4 | 7% |
Student > Bachelor | 4 | 7% |
Student > Doctoral Student | 3 | 5% |
Other | 10 | 18% |
Unknown | 8 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 17 | 30% |
Computer Science | 12 | 21% |
Biochemistry, Genetics and Molecular Biology | 8 | 14% |
Engineering | 5 | 9% |
Business, Management and Accounting | 2 | 4% |
Other | 4 | 7% |
Unknown | 8 | 14% |