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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Computational prediction of disease microRNAs in domestic animals
|
|---|---|
| Published in |
BMC Research Notes, June 2014
|
| DOI | 10.1186/1756-0500-7-403 |
| Pubmed ID | |
| Authors |
Teresia Buza, Mark Arick, Hui Wang, Daniel G Peterson |
| Abstract |
The most important means of identifying diseases before symptoms appear is through the discovery of disease-associated biomarkers. Recently, microRNAs (miRNAs) have become highly useful biomarkers of infectious, genetic and metabolic diseases in human but they have not been well studied in domestic animals. It is probable that many of the animal homologs of human disease-associated miRNAs may be involved in domestic animal diseases. Here we describe a computational biology study in which human disease miRNAs were utilized to predict orthologous miRNAs in cow, chicken, pig, horse, and dog. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 2 | 3% |
| Spain | 1 | 2% |
| Unknown | 59 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 20 | 32% |
| Student > Ph. D. Student | 9 | 15% |
| Student > Bachelor | 8 | 13% |
| Student > Master | 6 | 10% |
| Student > Doctoral Student | 3 | 5% |
| Other | 7 | 11% |
| Unknown | 9 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 15 | 24% |
| Veterinary Science and Veterinary Medicine | 11 | 18% |
| Medicine and Dentistry | 11 | 18% |
| Biochemistry, Genetics and Molecular Biology | 8 | 13% |
| Computer Science | 4 | 6% |
| Other | 2 | 3% |
| Unknown | 11 | 18% |
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 28 June 2014.
All research outputs
#15,302,068
of 22,757,541 outputs
Outputs from BMC Research Notes
#2,314
of 4,262 outputs
Outputs of similar age
#133,371
of 227,675 outputs
Outputs of similar age from BMC Research Notes
#54
of 100 outputs
Altmetric has tracked 22,757,541 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,262 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 33rd percentile – i.e., 33% 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 227,675 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 100 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.