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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Computational developments in microRNA-regulated protein-protein interactions
|
|---|---|
| Published in |
BMC Systems Biology, February 2014
|
| DOI | 10.1186/1752-0509-8-14 |
| Pubmed ID | |
| Authors |
Wei Zhu, Yi-Ping Phoebe Chen |
| Abstract |
Protein-protein interaction (PPI) is one of the most important functional components of a living cell. Recently, researchers have been interested in investigating the correlation between PPI and microRNA, which has been found to be a regulator at the post-transcriptional level. Studies on miRNA-regulated PPI networks will not only facilitate an understanding of the fine tuning role that miRNAs play in PPI networks, but will also provide potential candidates for tumor diagnosis. This review describes basic studies on the miRNA-regulated PPI network in the way of bioinformatics which includes constructing a miRNA-target protein network, describing the features of miRNA-regulated PPI networks and overviewing previous findings based on analysing miRNA-regulated PPI network features. |
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 % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 2% |
| Turkey | 1 | 2% |
| Unknown | 42 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 25% |
| Student > Master | 8 | 18% |
| Researcher | 5 | 11% |
| Student > Bachelor | 3 | 7% |
| Student > Doctoral Student | 2 | 5% |
| Other | 9 | 20% |
| Unknown | 6 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 17 | 39% |
| Biochemistry, Genetics and Molecular Biology | 8 | 18% |
| Computer Science | 5 | 11% |
| Engineering | 4 | 9% |
| Environmental Science | 1 | 2% |
| Other | 3 | 7% |
| Unknown | 6 | 14% |
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 10 February 2014.
All research outputs
#22,759,802
of 25,374,917 outputs
Outputs from BMC Systems Biology
#1,004
of 1,132 outputs
Outputs of similar age
#287,013
of 327,781 outputs
Outputs of similar age from BMC Systems Biology
#35
of 38 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,132 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 1st percentile – i.e., 1% 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 327,781 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.