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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Electrochemical detection of protein glycosylation using lectin and protein–gold affinity interactions
|
|---|---|
| Published in |
Analyst, January 2016
|
| DOI | 10.1039/c6an00528d |
| Pubmed ID | |
| Authors |
Sharda Yadav, Laura G. Carrascosa, Abu A. I. Sina, Muhammad J. A. Shiddiky, Michelle M. Hill, Matt Trau |
| Abstract |
We report a new method for the electrochemical detection of glycosylation on proteins, which relies on lectin-protein interaction on a bare gold electrode. The target protein isolated by immunoaffinity is directly adsorbed onto a gold surface and its glycosylation status is retrieved by subsequent addition of specific lectins. The adsorption and subsequent recognition process is monitored electrochemically in the presence of [Fe(CN)6](3-/4-) redox system. By decoupling target protein capture from glycosylation read-out steps, this approach circumvents unwanted antibody-lectin crosstalk while enabling specific glycosylation detection of a glycoprotein in serum-spiked samples in less than 1 h. |
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 % |
|---|---|---|
| Australia | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 18 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 5 | 28% |
| Student > Ph. D. Student | 4 | 22% |
| Student > Bachelor | 3 | 17% |
| Other | 1 | 6% |
| Student > Doctoral Student | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 3 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 28% |
| Engineering | 4 | 22% |
| Chemistry | 3 | 17% |
| Agricultural and Biological Sciences | 1 | 6% |
| Materials Science | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 3 | 17% |
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 17 March 2016.
All research outputs
#14,842,329
of 22,856,968 outputs
Outputs from Analyst
#3,666
of 5,801 outputs
Outputs of similar age
#218,948
of 393,628 outputs
Outputs of similar age from Analyst
#164
of 503 outputs
Altmetric has tracked 22,856,968 research outputs across all sources so far. This one is in the 33rd percentile – i.e., 33% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,801 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 34th percentile – i.e., 34% 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 393,628 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 503 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 64% of its contemporaries.