| Title |
Eugene – A Domain Specific Language for Specifying and Constraining Synthetic Biological Parts, Devices, and Systems
|
|---|---|
| Published in |
PLOS ONE, April 2011
|
| DOI | 10.1371/journal.pone.0018882 |
| Pubmed ID | |
| Authors |
Lesia Bilitchenko, Adam Liu, Sherine Cheung, Emma Weeding, Bing Xia, Mariana Leguia, J. Christopher Anderson, Douglas Densmore |
| Abstract |
Synthetic biological systems are currently created by an ad-hoc, iterative process of specification, design, and assembly. These systems would greatly benefit from a more formalized and rigorous specification of the desired system components as well as constraints on their composition. Therefore, the creation of robust and efficient design flows and tools is imperative. We present a human readable language (Eugene) that allows for the specification of synthetic biological designs based on biological parts, as well as provides a very expressive constraint system to drive the automatic creation of composite Parts (Devices) from a collection of individual Parts. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Spain | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 164 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 11 | 7% |
| United Kingdom | 3 | 2% |
| France | 2 | 1% |
| Canada | 2 | 1% |
| Austria | 1 | <1% |
| Portugal | 1 | <1% |
| Belgium | 1 | <1% |
| Germany | 1 | <1% |
| Spain | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 140 | 85% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 39 | 24% |
| Researcher | 38 | 23% |
| Student > Master | 27 | 16% |
| Student > Bachelor | 14 | 9% |
| Student > Doctoral Student | 9 | 5% |
| Other | 25 | 15% |
| Unknown | 12 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 59 | 36% |
| Computer Science | 28 | 17% |
| Biochemistry, Genetics and Molecular Biology | 24 | 15% |
| Engineering | 17 | 10% |
| Social Sciences | 3 | 2% |
| Other | 12 | 7% |
| Unknown | 21 | 13% |