| Title |
Compiler-aided systematic construction of large-scale DNA strand displacement circuits using unpurified components
|
|---|---|
| Published in |
Nature Communications, February 2017
|
| DOI | 10.1038/ncomms14373 |
| Pubmed ID | |
| Authors |
Anupama J. Thubagere, Chris Thachuk, Joseph Berleant, Robert F. Johnson, Diana A. Ardelean, Kevin M. Cherry, Lulu Qian |
| Abstract |
Biochemical circuits made of rationally designed DNA molecules are proofs of concept for embedding control within complex molecular environments. They hold promise for transforming the current technologies in chemistry, biology, medicine and material science by introducing programmable and responsive behaviour to diverse molecular systems. As the transformative power of a technology depends on its accessibility, two main challenges are an automated design process and simple experimental procedures. Here we demonstrate the use of circuit design software, combined with the use of unpurified strands and simplified experimental procedures, for creating a complex DNA strand displacement circuit that consists of 78 distinct species. We develop a systematic procedure for overcoming the challenges involved in using unpurified DNA strands. We also develop a model that takes synthesis errors into consideration and semi-quantitatively reproduces the experimental data. Our methods now enable even novice researchers to successfully design and construct complex DNA strand displacement circuits. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 72 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 21 | 29% |
| Student > Master | 8 | 11% |
| Researcher | 6 | 8% |
| Student > Bachelor | 5 | 7% |
| Professor > Associate Professor | 5 | 7% |
| Other | 9 | 13% |
| Unknown | 18 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 14 | 19% |
| Chemistry | 8 | 11% |
| Engineering | 7 | 10% |
| Agricultural and Biological Sciences | 7 | 10% |
| Computer Science | 6 | 8% |
| Other | 10 | 14% |
| Unknown | 20 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 50. 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 10 November 2018.
All research outputs
#712,994
of 22,955,959 outputs
Outputs from Nature Communications
#12,140
of 47,252 outputs
Outputs of similar age
#16,505
of 311,210 outputs
Outputs of similar age from Nature Communications
#302
of 926 outputs
Altmetric has tracked 22,955,959 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 47,252 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 55.8. This one has gotten more attention than average, scoring higher than 74% of its peers.
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We're also able to compare this research output to 926 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.