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CircPrimer: a software for annotating circRNAs and determining the specificity of circRNA primers

Overview of attention for article published in BMC Bioinformatics, August 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

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16 X users

Citations

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43 Mendeley
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Title
CircPrimer: a software for annotating circRNAs and determining the specificity of circRNA primers
Published in
BMC Bioinformatics, August 2018
DOI 10.1186/s12859-018-2304-1
Pubmed ID
Authors

Shanliang Zhong, Jinyan Wang, Qian Zhang, Hanzi Xu, Jifeng Feng

Abstract

Since circular RNAs (circRNAs) post-transcriptionally regulate gene expression, they have attracted increasing attention. However, there is no existing tool to annotate and extract spliced sequences for circRNAs and no tool to determine the specificity of circRNA primers. In this study, we present circPrimer, which allows users to search, annotate, and visualize circRNAs. Additionally, circPrimer enables users to extract the spliced sequences and genomic sequences of any circRNA, including novel circRNAs. Furthermore, circPrimer help users to design primers for circRNAs and to determine the specificity of the circRNA primers. CircPrimer is a user-friendly tool for exploring circRNAs that does not require special user skills.

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 23%
Researcher 9 21%
Student > Master 5 12%
Student > Bachelor 4 9%
Unknown 15 35%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 30%
Agricultural and Biological Sciences 6 14%
Computer Science 3 7%
Pharmacology, Toxicology and Pharmaceutical Science 1 2%
Unknown 20 47%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 13 February 2022.
All research outputs
#4,219,568
of 25,540,105 outputs
Outputs from BMC Bioinformatics
#1,417
of 7,717 outputs
Outputs of similar age
#74,704
of 342,023 outputs
Outputs of similar age from BMC Bioinformatics
#23
of 94 outputs
Altmetric has tracked 25,540,105 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,717 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 81% 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 342,023 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 78% of its contemporaries.
We're also able to compare this research output to 94 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.