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Mendeley readers
Attention Score in Context
| Title |
Photo-affinity labeling (PAL) in chemical proteomics: a handy tool to investigate protein-protein interactions (PPIs)
|
|---|---|
| Published in |
Proteome Science, June 2017
|
| DOI | 10.1186/s12953-017-0123-3 |
| Pubmed ID | |
| Authors |
Dhiraj P. Murale, Seong Cheol Hong, Md. Mamunul Haque, Jun-Seok Lee |
| Abstract |
Protein-protein interactions (PPIs) trigger a wide range of biological signaling pathways that are crucial for biomedical research and drug discovery. Various techniques have been used to study specific proteins, including affinity chromatography, activity-based probes, affinity-based probes and photo-affinity labeling (PAL). PAL has become one of the most powerful strategies to study PPIs. Traditional photocrosslinkers are used in PAL, including benzophenone, aryl azide, and diazirine. Upon photoirradiation, these photocrosslinkers (Pls) generate highly reactive species that react with adjacent molecules, resulting in a direct covalent modification. This review introduces recent examples of chemical proteomics study using PAL for PPIs. |
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 410 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 410 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 100 | 24% |
| Researcher | 55 | 13% |
| Student > Master | 52 | 13% |
| Student > Bachelor | 38 | 9% |
| Student > Postgraduate | 15 | 4% |
| Other | 43 | 10% |
| Unknown | 107 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 163 | 40% |
| Biochemistry, Genetics and Molecular Biology | 75 | 18% |
| Agricultural and Biological Sciences | 16 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 11 | 3% |
| Engineering | 9 | 2% |
| Other | 22 | 5% |
| Unknown | 114 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 27 February 2024.
All research outputs
#3,574,284
of 25,440,205 outputs
Outputs from Proteome Science
#11
of 209 outputs
Outputs of similar age
#62,043
of 329,207 outputs
Outputs of similar age from Proteome Science
#1
of 7 outputs
Altmetric has tracked 25,440,205 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 209 research outputs from this source. They receive a mean Attention Score of 2.7. This one has done particularly well, scoring higher than 95% 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 329,207 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them