| Title |
SBOL Visual: A Graphical Language for Genetic Designs
|
|---|---|
| Published in |
PLoS Biology, December 2015
|
| DOI | 10.1371/journal.pbio.1002310 |
| Pubmed ID | |
| Authors |
Jacqueline Y Quinn, Robert Sidney Cox, Aaron Adler, Jacob Beal, Swapnil Bhatia, Yizhi Cai, Joanna Chen, Kevin Clancy, Michal Galdzicki, Nathan J Hillson, Nicolas Le Novère, Akshay J Maheshwari, James Alastair McLaughlin, Chris J Myers, Umesh P, Matthew Pocock, Cesar Rodriguez, Larisa Soldatova, Guy-Bart V Stan, Neil Swainston, Anil Wipat, Herbert M Sauro |
| Abstract |
Synthetic Biology Open Language (SBOL) Visual is a graphical standard for genetic engineering. It consists of symbols representing DNA subsequences, including regulatory elements and DNA assembly features. These symbols can be used to draw illustrations for communication and instruction, and as image assets for computer-aided design. SBOL Visual is a community standard, freely available for personal, academic, and commercial use (Creative Commons CC0 license). We provide prototypical symbol images that have been used in scientific publications and software tools. We encourage users to use and modify them freely, and to join the SBOL Visual community: http://www.sbolstandard.org/visual. |
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X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 33 | 32% |
| United Kingdom | 9 | 9% |
| France | 4 | 4% |
| Spain | 3 | 3% |
| India | 3 | 3% |
| Italy | 2 | 2% |
| Germany | 2 | 2% |
| Australia | 2 | 2% |
| Chile | 2 | 2% |
| Other | 11 | 11% |
| Unknown | 33 | 32% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 81 | 78% |
| Scientists | 18 | 17% |
| Science communicators (journalists, bloggers, editors) | 4 | 4% |
| Practitioners (doctors, other healthcare professionals) | 1 | <1% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 2% |
| United Kingdom | 2 | 1% |
| Sweden | 1 | <1% |
| Netherlands | 1 | <1% |
| Spain | 1 | <1% |
| Denmark | 1 | <1% |
| Czechia | 1 | <1% |
| Bulgaria | 1 | <1% |
| Belgium | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 140 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 39 | 26% |
| Student > Ph. D. Student | 29 | 19% |
| Student > Bachelor | 17 | 11% |
| Student > Master | 15 | 10% |
| Professor | 8 | 5% |
| Other | 19 | 13% |
| Unknown | 25 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 41 | 27% |
| Agricultural and Biological Sciences | 41 | 27% |
| Engineering | 12 | 8% |
| Computer Science | 8 | 5% |
| Immunology and Microbiology | 3 | 2% |
| Other | 14 | 9% |
| Unknown | 33 | 22% |