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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Using protein microarray technology to screen anti-ERCC1 monoclonal antibodies for specificity and applications in pathology
|
|---|---|
| Published in |
BMC Biotechnology, November 2012
|
| DOI | 10.1186/1472-6750-12-88 |
| Pubmed ID | |
| Authors |
Donghui Ma, Dror Baruch, Youmin Shu, Kehu Yuan, Zairen Sun, Kaiyan Ma, Toan Hoang, Wei Fu, Li Min, Zhu-Sheng Lan, Fangxun Wang, Lori Mull, Wei-Wu He |
| Abstract |
An antibody with cross-reactivity can create unexpected side effects or false diagnostic reports if used for clinical purposes. ERCC1 is being explored as a predictive diagnostic biomarker for cisplatin-based chemotherapy. High ERCC1 expression is linked to drug resistance on cisplatin-based chemotherapy. 8F1 is one of the most commonly used monoclonal antibodies for evaluating ERCC1 expression levels in lung cancer patient tissues, but it has been noted that this antibody cross-reacts with an unknown protein. |
X Demographics
The data shown below were collected from the profiles of 4 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 | 3 | 75% |
| Japan | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 40 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 30% |
| Student > Ph. D. Student | 6 | 15% |
| Student > Bachelor | 4 | 10% |
| Student > Master | 4 | 10% |
| Professor > Associate Professor | 2 | 5% |
| Other | 3 | 8% |
| Unknown | 9 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 15 | 38% |
| Medicine and Dentistry | 8 | 20% |
| Biochemistry, Genetics and Molecular Biology | 3 | 8% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 5% |
| Psychology | 1 | 3% |
| Other | 2 | 5% |
| Unknown | 9 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 25 June 2017.
All research outputs
#2,401,799
of 22,687,320 outputs
Outputs from BMC Biotechnology
#71
of 935 outputs
Outputs of similar age
#24,164
of 275,937 outputs
Outputs of similar age from BMC Biotechnology
#1
of 14 outputs
Altmetric has tracked 22,687,320 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 935 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has done particularly well, scoring higher than 92% 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 275,937 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.