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Mendeley readers
Attention Score in Context
| Title |
Methods and matrices: approaches to identifying miRNAs for Nasopharyngeal carcinoma
|
|---|---|
| Published in |
Journal of Translational Medicine, January 2014
|
| DOI | 10.1186/1479-5876-12-3 |
| Pubmed ID | |
| Authors |
Jordan L Plieskatt, Gabriel Rinaldi, Yanjung Feng, Paul H Levine, Samantha Easley, Elizabeth Martinez, Salman Hashmi, Nader Sadeghi, Paul J Brindley, Jeffrey M Bethony, Jason P Mulvenna |
| Abstract |
Nasopharyngeal carcinoma (NPC) is a solid tumor of the head and neck. Multimodal therapy is highly effective when NPC is detected early. However, due to the location of the tumor and the absence of clinical signs, early detection is difficult, making a biomarker for the early detection of NPC a priority. The dysregulation of small non-coding RNAs (miRNAs) during carcinogenesis is the focus of much current biomarker research. Herein, we examine several miRNA discovery methods using two sample matrices to identify circulating miRNAs (c-miRNAs) associated with NPC. |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Uruguay | 2 | 4% |
| Malaysia | 1 | 2% |
| Denmark | 1 | 2% |
| United States | 1 | 2% |
| Unknown | 45 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 24% |
| Professor > Associate Professor | 7 | 14% |
| Researcher | 6 | 12% |
| Student > Master | 6 | 12% |
| Student > Bachelor | 5 | 10% |
| Other | 7 | 14% |
| Unknown | 7 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 13 | 26% |
| Medicine and Dentistry | 12 | 24% |
| Biochemistry, Genetics and Molecular Biology | 8 | 16% |
| Veterinary Science and Veterinary Medicine | 2 | 4% |
| Engineering | 2 | 4% |
| Other | 5 | 10% |
| Unknown | 8 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 12 August 2020.
All research outputs
#7,438,092
of 22,738,543 outputs
Outputs from Journal of Translational Medicine
#1,235
of 3,975 outputs
Outputs of similar age
#91,778
of 304,804 outputs
Outputs of similar age from Journal of Translational Medicine
#50
of 114 outputs
Altmetric has tracked 22,738,543 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,975 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has gotten more attention than average, scoring higher than 64% 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 304,804 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 114 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 55% of its contemporaries.