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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Diverse functions of miR-373 in cancer
|
|---|---|
| Published in |
Journal of Translational Medicine, May 2015
|
| DOI | 10.1186/s12967-015-0523-z |
| Pubmed ID | |
| Authors |
Furong Wei, Chuanhua Cao, Xiaoqun Xu, Junfu Wang |
| Abstract |
MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression post-transcriptionally. They are involved in almost all cellular processes, and many have been described as potential oncogenes or tumor suppressors. MicroRNA-373 (miR-373), which was first identified as a human embryonic stem cell (ESC)-specific miRNA, is suggested to be implicated in the regulation of cell proliferation, apoptosis, senescence, migration and invasion, as well as DNA damage repair following hypoxia stress. Deregulation of miR-373 has been demonstrated in a number of cancers, whether it acts as an oncogene or a tumor suppressor, however, seems to be context dependent. In this review, we focus on the diverse functions of miR-373 and its implication in cancers. |
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 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Luxembourg | 1 | 2% |
| Unknown | 52 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 23% |
| Student > Master | 11 | 21% |
| Student > Bachelor | 9 | 17% |
| Researcher | 7 | 13% |
| Other | 2 | 4% |
| Other | 3 | 6% |
| Unknown | 9 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 13 | 25% |
| Agricultural and Biological Sciences | 10 | 19% |
| Medicine and Dentistry | 9 | 17% |
| Nursing and Health Professions | 2 | 4% |
| Immunology and Microbiology | 2 | 4% |
| Other | 6 | 11% |
| Unknown | 11 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 21 May 2015.
All research outputs
#14,812,046
of 22,805,349 outputs
Outputs from Journal of Translational Medicine
#1,972
of 3,991 outputs
Outputs of similar age
#147,672
of 266,611 outputs
Outputs of similar age from Journal of Translational Medicine
#58
of 96 outputs
Altmetric has tracked 22,805,349 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,991 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 44th percentile – i.e., 44% 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 266,611 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 96 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.