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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Determining the Effects of Membrane-Interacting Peptides on Membrane Integrity.
|
|---|---|
| Chapter number | 6 |
| Book title |
Cell-Penetrating Peptides
|
| Published in |
Methods in molecular biology, January 2015
|
| DOI | 10.1007/978-1-4939-2806-4_6 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-2805-7, 978-1-4939-2806-4
|
| Authors |
Wimley, William C, William C. Wimley |
| Editors |
Ülo Langel |
| Abstract |
In the study of cell-penetrating and membrane-translocating peptides, a fundamental question occurs as to the contribution arising from fundamental peptide-membrane interactions, relative to the contribution arising from the biology and energy of the cell, mostly occurring in the form of endocytosis and subsequent events. A commonly used approach to begin addressing these mechanistic questions is to measure the degree to which peptides can interact with, and physically disrupt, the integrity of synthetic lipid bilayers. Here, we describe a set of experimental methods that can be used to measure the potency, kinetics, transience, and the effective size of peptide-induced membrane disruption. |
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 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 32 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 34% |
| Researcher | 7 | 22% |
| Student > Doctoral Student | 2 | 6% |
| Student > Postgraduate | 2 | 6% |
| Professor | 2 | 6% |
| Other | 3 | 9% |
| Unknown | 5 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 14 | 44% |
| Chemistry | 6 | 19% |
| Agricultural and Biological Sciences | 5 | 16% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 3% |
| Unknown | 6 | 19% |
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 24 July 2015.
All research outputs
#20,283,046
of 22,817,213 outputs
Outputs from Methods in molecular biology
#9,911
of 13,121 outputs
Outputs of similar age
#295,832
of 353,109 outputs
Outputs of similar age from Methods in molecular biology
#636
of 997 outputs
Altmetric has tracked 22,817,213 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 13,121 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 353,109 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 997 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.