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Attention Score in Context
Title |
Connecting rules from paired miRNA and mRNA expression data sets of HCV patients to detect both inverse and positive regulatory relationships
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Published in |
BMC Genomics, January 2015
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DOI | 10.1186/1471-2164-16-s2-s11 |
Pubmed ID | |
Authors |
Renhua Song, Qian Liu, Tao Liu, Jinyan Li |
Abstract |
Intensive research based on the inverse expression relationship has been undertaken to discover the miRNA-mRNA regulatory modules involved in the infection of Hepatitis C virus (HCV), the leading cause of chronic liver diseases. However, biological studies in other fields have found that inverse expression relationship is not the only regulatory relationship between miRNAs and their targets, and some miRNAs can positively regulate a mRNA by binding at the 5' UTR of the mRNA. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
France | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 67% |
Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 28 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 7 | 25% |
Student > Ph. D. Student | 5 | 18% |
Student > Bachelor | 4 | 14% |
Student > Postgraduate | 3 | 11% |
Student > Master | 3 | 11% |
Other | 4 | 14% |
Unknown | 2 | 7% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 8 | 29% |
Biochemistry, Genetics and Molecular Biology | 7 | 25% |
Agricultural and Biological Sciences | 4 | 14% |
Computer Science | 4 | 14% |
Immunology and Microbiology | 1 | 4% |
Other | 1 | 4% |
Unknown | 3 | 11% |
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 26 February 2015.
All research outputs
#15,325,572
of 22,793,427 outputs
Outputs from BMC Genomics
#6,689
of 10,648 outputs
Outputs of similar age
#209,165
of 351,785 outputs
Outputs of similar age from BMC Genomics
#177
of 276 outputs
Altmetric has tracked 22,793,427 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 10,648 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 29th percentile – i.e., 29% 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 351,785 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 276 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.