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Mendeley readers
Attention Score in Context
| Chapter title |
Lessons from an α-Helical Membrane Enzyme: Expression, Purification, and Detergent Optimization for Biophysical and Structural Characterization.
|
|---|---|
| Chapter number | 18 |
| Book title |
Heterologous Expression of Membrane Proteins
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-3637-3_18 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3635-9, 978-1-4939-3637-3
|
| Authors |
Jennifer L. Johnson, Sibel Kalyoncu, Raquel L. Lieberman |
| Editors |
Isabelle Mus-Veteau |
| Abstract |
This chapter outlines the protocol developed in our lab to produce a multipass α-helical membrane protein. We present our work flow, from ortholog selection to protein purification, including molecular biology for plasmid construction, protein expression in E. coli, membrane isolation and detergent solubilization, protein purification and tag removal, biophysical assessment of protein stability in different detergents, and detergent concentration determination using thin-layer chromatography. We focus on results from our ongoing work with intramembrane aspartyl proteases from archaeal organisms. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 9 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 56% |
| Student > Doctoral Student | 1 | 11% |
| Professor > Associate Professor | 1 | 11% |
| Student > Ph. D. Student | 1 | 11% |
| Unknown | 1 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 33% |
| Chemical Engineering | 1 | 11% |
| Agricultural and Biological Sciences | 1 | 11% |
| Computer Science | 1 | 11% |
| Neuroscience | 1 | 11% |
| Other | 1 | 11% |
| Unknown | 1 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 2017.
All research outputs
#20,341,859
of 22,888,307 outputs
Outputs from Methods in molecular biology
#9,921
of 13,132 outputs
Outputs of similar age
#330,770
of 393,716 outputs
Outputs of similar age from Methods in molecular biology
#1,054
of 1,471 outputs
Altmetric has tracked 22,888,307 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,132 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 393,716 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,471 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.