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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A synthetic biology approach to self-regulatory recombinant protein production in Escherichia coli
|
|---|---|
| Published in |
Journal of Biological Engineering, December 2012
|
| DOI | 10.1186/1754-1611-6-2 |
| Pubmed ID | |
| Authors |
Martin Dragosits, Daniel Nicklas, Ilias Tagkopoulos |
| Abstract |
Recombinant protein production is a process of great industrial interest, with products that range from pharmaceuticals to biofuels. Since high level production of recombinant protein imposes significant stress in the host organism, several methods have been developed over the years to optimize protein production. So far, these trial-and-error techniques have proved laborious and sensitive to process parameters, while there has been no attempt to address the problem by applying Synthetic Biology principles and methods, such as integration of standardized parts in novel synthetic circuits. |
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% |
| Unknown | 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 168 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 2% |
| United Kingdom | 3 | 2% |
| Uruguay | 1 | <1% |
| Austria | 1 | <1% |
| Iran, Islamic Republic of | 1 | <1% |
| Netherlands | 1 | <1% |
| Belgium | 1 | <1% |
| Mexico | 1 | <1% |
| Unknown | 155 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 37 | 22% |
| Researcher | 32 | 19% |
| Student > Master | 26 | 15% |
| Student > Bachelor | 14 | 8% |
| Student > Postgraduate | 7 | 4% |
| Other | 21 | 13% |
| Unknown | 31 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 61 | 36% |
| Biochemistry, Genetics and Molecular Biology | 34 | 20% |
| Engineering | 18 | 11% |
| Computer Science | 5 | 3% |
| Social Sciences | 4 | 2% |
| Other | 12 | 7% |
| Unknown | 34 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 19 December 2018.
All research outputs
#6,378,772
of 22,664,267 outputs
Outputs from Journal of Biological Engineering
#99
of 258 outputs
Outputs of similar age
#66,878
of 277,081 outputs
Outputs of similar age from Journal of Biological Engineering
#12
of 24 outputs
Altmetric has tracked 22,664,267 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 258 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one has gotten more attention than average, scoring higher than 60% 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 277,081 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 24 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 50% of its contemporaries.