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PrimerView: high-throughput primer design and visualization

Overview of attention for article published in Source Code for Biology and Medicine, June 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#7 of 127)
  • High Attention Score compared to outputs of the same age (91st percentile)

Mentioned by

blogs
2 blogs
twitter
6 X users
weibo
1 weibo user

Citations

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9 Dimensions

Readers on

mendeley
56 Mendeley
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Title
PrimerView: high-throughput primer design and visualization
Published in
Source Code for Biology and Medicine, June 2015
DOI 10.1186/s13029-015-0038-2
Pubmed ID
Authors

Damien M. O’Halloran

Abstract

High-throughput primer design is routinely performed in a wide number of molecular applications including genotyping specimens using traditional PCR techniques as well as assembly PCR, nested PCR, and primer walking experiments. Batch primer design is also required in validation experiments from RNA-seq transcriptome sequencing projects, as well as in generating probes for microarray experiments. The growing popularity of next generation sequencing and microarray technology has created a greater need for more primer design tools to validate large numbers of candidate genes and markers. To meet these demands I here present a tool called PrimerView that designs forward and reverse primers from multi-sequence datasets, and generates graphical outputs that map the position and distribution of primers to the target sequence. This module operates from the command-line and can collect user-defined input for the design phase of each primer. PrimerView is a straightforward to use module that implements a primer design algorithm to return forward and reverse primers from any number of FASTA formatted sequences to generate text based output of the features for each primer, and also graphical outputs that map the designed primers to the target sequence. PrimerView is freely available without restrictions.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Denmark 1 2%
Switzerland 1 2%
Brazil 1 2%
Unknown 51 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 29%
Student > Ph. D. Student 15 27%
Student > Master 6 11%
Student > Bachelor 5 9%
Lecturer 3 5%
Other 7 13%
Unknown 4 7%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 21 38%
Agricultural and Biological Sciences 17 30%
Computer Science 4 7%
Environmental Science 2 4%
Chemical Engineering 1 2%
Other 4 7%
Unknown 7 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. 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 26 April 2018.
All research outputs
#1,777,785
of 23,567,572 outputs
Outputs from Source Code for Biology and Medicine
#7
of 127 outputs
Outputs of similar age
#23,647
of 268,423 outputs
Outputs of similar age from Source Code for Biology and Medicine
#1
of 2 outputs
Altmetric has tracked 23,567,572 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 127 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done particularly well, scoring higher than 94% 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 268,423 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 2 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