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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Identification of candidate miRNA biomarkers from miRNA regulatory network with application to prostate cancer
|
|---|---|
| Published in |
Journal of Translational Medicine, March 2014
|
| DOI | 10.1186/1479-5876-12-66 |
| Pubmed ID | |
| Authors |
Wenyu Zhang, Jin Zang, Xinhua Jing, Zhandong Sun, Wenying Yan, Dongrong Yang, Feng Guo, Bairong Shen |
| Abstract |
MicroRNAs (miRNAs) are a class of non-coding regulatory RNAs approximately 22 nucleotides in length that play a role in a wide range of biological processes. Abnormal miRNA function has been implicated in various human cancers including prostate cancer (PCa). Altered miRNA expression may serve as a biomarker for cancer diagnosis and treatment. However, limited data are available on the role of cancer-specific miRNAs. Integrative computational bioinformatics approaches are effective for the detection of potential outlier miRNAs in cancer. |
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 % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 1% |
| Denmark | 1 | 1% |
| Poland | 1 | 1% |
| Unknown | 85 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 26 | 30% |
| Researcher | 12 | 14% |
| Student > Postgraduate | 7 | 8% |
| Professor > Associate Professor | 6 | 7% |
| Student > Doctoral Student | 5 | 6% |
| Other | 19 | 22% |
| Unknown | 13 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 23 | 26% |
| Biochemistry, Genetics and Molecular Biology | 19 | 22% |
| Computer Science | 12 | 14% |
| Medicine and Dentistry | 9 | 10% |
| Engineering | 3 | 3% |
| Other | 5 | 6% |
| Unknown | 17 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 06 September 2014.
All research outputs
#18,366,246
of 22,747,498 outputs
Outputs from Journal of Translational Medicine
#2,944
of 3,977 outputs
Outputs of similar age
#160,530
of 220,818 outputs
Outputs of similar age from Journal of Translational Medicine
#31
of 55 outputs
Altmetric has tracked 22,747,498 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,977 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one is in the 16th percentile – i.e., 16% 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 220,818 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.