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Attention Score in Context
Title |
Identification of distinct miRNA target regulation between breast cancer molecular subtypes using AGO2-PAR-CLIP and patient datasets
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Published in |
Genome Biology, January 2014
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DOI | 10.1186/gb-2014-15-1-r9 |
Pubmed ID | |
Authors |
Thalia A Farazi, Jelle J ten Hoeve, Miguel Brown, Aleksandra Mihailovic, Hugo M Horlings, Marc J van de Vijver, Thomas Tuschl, Lodewyk FA Wessels |
Abstract |
Various microRNAs (miRNAs) are up- or downregulated in tumors. However, the repression of cognate miRNA targets responsible for the phenotypic effects of this dysregulation in patients remains largely unexplored. To define miRNA targets and associated pathways, together with their relationship to outcome in breast cancer, we integrated patient-paired miRNA-mRNA expression data with a set of validated miRNA targets and pathway inference. |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 4 | 50% |
United States | 3 | 38% |
France | 1 | 13% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 5 | 63% |
Scientists | 2 | 25% |
Science communicators (journalists, bloggers, editors) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Denmark | 2 | 2% |
Germany | 1 | <1% |
France | 1 | <1% |
United Kingdom | 1 | <1% |
Italy | 1 | <1% |
Mexico | 1 | <1% |
United States | 1 | <1% |
Unknown | 101 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 29 | 27% |
Student > Ph. D. Student | 26 | 24% |
Student > Master | 15 | 14% |
Student > Bachelor | 9 | 8% |
Student > Doctoral Student | 7 | 6% |
Other | 16 | 15% |
Unknown | 7 | 6% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 42 | 39% |
Biochemistry, Genetics and Molecular Biology | 27 | 25% |
Medicine and Dentistry | 15 | 14% |
Computer Science | 8 | 7% |
Pharmacology, Toxicology and Pharmaceutical Science | 2 | 2% |
Other | 6 | 6% |
Unknown | 9 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 12 November 2014.
All research outputs
#7,263,349
of 25,371,288 outputs
Outputs from Genome Biology
#3,289
of 4,467 outputs
Outputs of similar age
#79,239
of 318,504 outputs
Outputs of similar age from Genome Biology
#95
of 115 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 26th percentile – i.e., 26% 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 318,504 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 115 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.