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A short guide to long non-coding RNA gene nomenclature

Overview of attention for article published in Human Genomics, April 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

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20 X users
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7 Wikipedia pages

Citations

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108 Dimensions

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118 Mendeley
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5 CiteULike
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Title
A short guide to long non-coding RNA gene nomenclature
Published in
Human Genomics, April 2014
DOI 10.1186/1479-7364-8-7
Pubmed ID
Authors

Mathew W Wright

Abstract

The HUGO Gene Nomenclature Committee (HGNC) is the only organisation authorised to assign standardised nomenclature to human genes. Of the 38,000 approved gene symbols in our database (http://www.genenames.org), the majority represent protein-coding (pc) genes; however, we also name pseudogenes, phenotypic loci, some genomic features, and to date have named more than 8,500 human non-protein coding RNA (ncRNA) genes and ncRNA pseudogenes. We have already established unique names for most of the small ncRNA genes by working with experts for each class. Small ncRNAs can be defined into their respective classes by their shared homology and common function. In contrast, long non-coding RNA (lncRNA) genes represent a disparate set of loci related only by their size, more than 200 bases in length, share no conserved sequence homology, and have variable functions. As with pc genes, wherever possible, lncRNAs are named based on the known function of their product; a short guide is presented herein to help authors when developing novel gene symbols for lncRNAs with characterised function. Researchers must contact the HGNC with their suggestions prior to publication, to check whether the proposed gene symbol can be approved. Although thousands of lncRNAs have been predicted in the human genome, for the vast majority their function remains unresolved. lncRNA genes with no known function are named based on their genomic context. Working with lncRNA researchers, the HGNC aims to provide unique and, wherever possible, meaningful gene symbols to all lncRNA genes.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 2 2%
United Kingdom 1 <1%
Canada 1 <1%
Spain 1 <1%
Japan 1 <1%
United States 1 <1%
Luxembourg 1 <1%
Unknown 110 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 20%
Student > Ph. D. Student 22 19%
Student > Master 16 14%
Student > Bachelor 10 8%
Student > Doctoral Student 7 6%
Other 24 20%
Unknown 15 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 42 36%
Biochemistry, Genetics and Molecular Biology 34 29%
Medicine and Dentistry 12 10%
Neuroscience 3 3%
Chemistry 2 2%
Other 7 6%
Unknown 18 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 September 2023.
All research outputs
#2,609,452
of 25,436,226 outputs
Outputs from Human Genomics
#70
of 564 outputs
Outputs of similar age
#25,790
of 241,429 outputs
Outputs of similar age from Human Genomics
#1
of 5 outputs
Altmetric has tracked 25,436,226 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 564 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 87% of its peers.
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 241,429 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 89% of its contemporaries.
We're also able to compare this research output to 5 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