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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Selected Reaction Monitoring (SRM) Analysis of Epidermal Growth Factor Receptor (EGFR) in Formalin Fixed Tumor Tissue
|
|---|---|
| Published in |
Clinical Proteomics, May 2012
|
| DOI | 10.1186/1559-0275-9-5 |
| Pubmed ID | |
| Authors |
Todd Hembrough, Sheeno Thyparambil, Wei-Li Liao, Marlene M Darfler, Joseph Abdo, Kathleen M Bengali, Paul Taylor, Jiefei Tong, Humberto Lara-Guerra, Thomas K Waddell, Michael F Moran, Ming-Sound Tsao, David B Krizman, Jon Burrows |
| Abstract |
Analysis of key therapeutic targets such as epidermal growth factor receptor (EGFR) in clinical tissue samples is typically done by immunohistochemistry (IHC) and is only subjectively quantitative through a narrow dynamic range. The development of a standardized, highly-sensitive, linear, and quantitative assay for EGFR for use in patient tumor tissue carries high potential for identifying those patients most likely to benefit from EGFR-targeted therapies. |
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% |
| United Kingdom | 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 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 3% |
| Switzerland | 1 | 1% |
| Unknown | 69 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 23 | 32% |
| Student > Ph. D. Student | 17 | 24% |
| Other | 6 | 8% |
| Professor > Associate Professor | 3 | 4% |
| Student > Master | 3 | 4% |
| Other | 8 | 11% |
| Unknown | 12 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 24 | 33% |
| Biochemistry, Genetics and Molecular Biology | 15 | 21% |
| Medicine and Dentistry | 7 | 10% |
| Chemistry | 5 | 7% |
| Computer Science | 3 | 4% |
| Other | 5 | 7% |
| Unknown | 13 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 13 November 2019.
All research outputs
#6,378,944
of 22,664,644 outputs
Outputs from Clinical Proteomics
#76
of 279 outputs
Outputs of similar age
#44,389
of 163,491 outputs
Outputs of similar age from Clinical Proteomics
#1
of 2 outputs
Altmetric has tracked 22,664,644 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 279 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has gotten more attention than average, scoring higher than 71% 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 163,491 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 2 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