↓ Skip to main content

Long noncoding RNAs, emerging players in muscle differentiation and disease

Overview of attention for article published in Skeletal Muscle, March 2014
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (53rd percentile)

Mentioned by

twitter
4 tweeters

Citations

dimensions_citation
77 Dimensions

Readers on

mendeley
149 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Long noncoding RNAs, emerging players in muscle differentiation and disease
Published in
Skeletal Muscle, March 2014
DOI 10.1186/2044-5040-4-8
Pubmed ID
Authors

Maria Victoria Neguembor, Mathivanan Jothi, Davide Gabellini

Abstract

The vast majority of the mammalian genome is transcribed giving rise to many different types of noncoding RNAs. Among them, long noncoding RNAs are the most numerous and functionally versatile class. Indeed, the lncRNA repertoire might be as rich as the proteome. LncRNAs have emerged as key regulators of gene expression at multiple levels. They play important roles in the regulation of development, differentiation and maintenance of cell identity and they also contribute to disease. In this review, we present recent advances in the biology of lncRNAs in muscle development and differentiation. We will also discuss the contribution of lncRNAs to muscle disease with a particular focus on Duchenne and facioscapulohumeral muscular dystrophies.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 149 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 1%
Brazil 1 <1%
Germany 1 <1%
Canada 1 <1%
Japan 1 <1%
Unknown 143 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 37 25%
Student > Ph. D. Student 32 21%
Student > Master 16 11%
Student > Bachelor 13 9%
Professor 11 7%
Other 22 15%
Unknown 18 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 57 38%
Biochemistry, Genetics and Molecular Biology 51 34%
Medicine and Dentistry 7 5%
Neuroscience 3 2%
Sports and Recreations 2 1%
Other 6 4%
Unknown 23 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 15 April 2014.
All research outputs
#12,291,451
of 21,362,911 outputs
Outputs from Skeletal Muscle
#254
of 345 outputs
Outputs of similar age
#96,003
of 206,913 outputs
Outputs of similar age from Skeletal Muscle
#1
of 1 outputs
Altmetric has tracked 21,362,911 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 345 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one is in the 25th percentile – i.e., 25% 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 206,913 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them