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Mendeley readers
Attention Score in Context
| Chapter title |
Optimization of Membrane Protein Production Using Titratable Strains of E. coli
|
|---|---|
| Chapter number | 6 |
| Book title |
Heterologous Gene Expression in E.coli
|
| Published in |
Methods in molecular biology, January 2017
|
| DOI | 10.1007/978-1-4939-6887-9_6 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6885-5, 978-1-4939-6887-9, 978-1-4939-6885-5, 978-1-4939-6887-9
|
| Authors |
Rosa Morra, Kate Young, David Casas-Mao, Neil Dixon, Louise E. Bird |
| Editors |
Nicola A. Burgess-Brown |
| Abstract |
The heterologous expression of membrane proteins driven by T7 RNA polymerase in E. coli is often limited by a mismatch between the transcriptional and translational rates resulting in saturation of the Sec translocon and non-insertion of the membrane protein. In order to optimize the levels of folded, functional inserted protein, it is important to correct this mismatch. In this protocol, we describe the use of titratable strains of E. coli where two small-molecule inducers are used in a bi-variate analysis to optimize the expression levels by fine tuning the transcriptional and translational rates of an eGFP-tagged membrane protein. |
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 % |
|---|---|---|
| Australia | 1 | 33% |
| Switzerland | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 33% |
| Members of the public | 1 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 7 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 2 | 29% |
| Student > Ph. D. Student | 1 | 14% |
| Lecturer > Senior Lecturer | 1 | 14% |
| Unknown | 3 | 43% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 2 | 29% |
| Agricultural and Biological Sciences | 1 | 14% |
| Unknown | 4 | 57% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 21 February 2018.
All research outputs
#15,704,531
of 25,656,290 outputs
Outputs from Methods in molecular biology
#4,493
of 14,318 outputs
Outputs of similar age
#233,355
of 423,400 outputs
Outputs of similar age from Methods in molecular biology
#362
of 1,088 outputs
Altmetric has tracked 25,656,290 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,318 research outputs from this source. They receive a mean Attention Score of 3.5. This one has gotten more attention than average, scoring higher than 68% 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 423,400 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,088 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 66% of its contemporaries.