Synthetic Biology
Springer New York
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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Automated Visualization of Genetic Designs Using DNAplotlib
|
|---|---|
| Book title |
Synthetic Biology
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7795-6_22 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7794-9, 978-1-4939-7795-6
|
| Authors |
Bartoli, Vittorio, Dixon, Daniel O R, Gorochowski, Thomas E, Vittorio Bartoli, Daniel O. R. Dixon, Thomas E. Gorochowski |
| Abstract |
Visualization of complex genetic systems can help efficiently communicate important design features and clearly illustrate overall structures. To aid in the creation of such diagrams, standards such as the Synthetic Biology Open Language Visual (SBOLv) have been established to ensure that specific symbols and shapes convey the same meaning for genetic parts across the field. Here, we describe several ways that the computational tool DNAplotlib can be used to automate the generation of SBOLv standard-compliant diagrams covering simple genetic designs to large libraries of genetic constructs. |
X Demographics
The data shown below were collected from the profiles of 17 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 Kingdom | 4 | 24% |
| Germany | 2 | 12% |
| Bolivia, Plurinational State of | 1 | 6% |
| Ireland | 1 | 6% |
| United States | 1 | 6% |
| Denmark | 1 | 6% |
| Portugal | 1 | 6% |
| Netherlands | 1 | 6% |
| Unknown | 5 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 9 | 53% |
| Members of the public | 6 | 35% |
| Science communicators (journalists, bloggers, editors) | 2 | 12% |
Mendeley readers
The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 8 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 63% |
| Student > Bachelor | 1 | 13% |
| Student > Doctoral Student | 1 | 13% |
| Unknown | 1 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 50% |
| Agricultural and Biological Sciences | 1 | 13% |
| Engineering | 1 | 13% |
| Unknown | 2 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 May 2018.
All research outputs
#3,346,384
of 24,133,587 outputs
Outputs from Methods in molecular biology
#728
of 13,615 outputs
Outputs of similar age
#73,802
of 450,196 outputs
Outputs of similar age from Methods in molecular biology
#52
of 1,483 outputs
Altmetric has tracked 24,133,587 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,615 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 450,196 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 1,483 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.