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Primer-BLAST: A tool to design target-specific primers for polymerase chain reaction

Overview of attention for article published in BMC Bioinformatics, June 2012
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

blogs
1 blog
twitter
21 tweeters
patent
9 patents
facebook
3 Facebook pages

Citations

dimensions_citation
2674 Dimensions

Readers on

mendeley
3603 Mendeley
citeulike
7 CiteULike
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Title
Primer-BLAST: A tool to design target-specific primers for polymerase chain reaction
Published in
BMC Bioinformatics, June 2012
DOI 10.1186/1471-2105-13-134
Pubmed ID
Authors

Jian Ye, George Coulouris, Irena Zaretskaya, Ioana Cutcutache, Steve Rozen, Thomas L Madden

Abstract

Choosing appropriate primers is probably the single most important factor affecting the polymerase chain reaction (PCR). Specific amplification of the intended target requires that primers do not have matches to other targets in certain orientations and within certain distances that allow undesired amplification. The process of designing specific primers typically involves two stages. First, the primers flanking regions of interest are generated either manually or using software tools; then they are searched against an appropriate nucleotide sequence database using tools such as BLAST to examine the potential targets. However, the latter is not an easy process as one needs to examine many details between primers and targets, such as the number and the positions of matched bases, the primer orientations and distance between forward and reverse primers. The complexity of such analysis usually makes this a time-consuming and very difficult task for users, especially when the primers have a large number of hits. Furthermore, although the BLAST program has been widely used for primer target detection, it is in fact not an ideal tool for this purpose as BLAST is a local alignment algorithm and does not necessarily return complete match information over the entire primer range.

Twitter Demographics

The data shown below were collected from the profiles of 21 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 3,603 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 16 <1%
United States 16 <1%
Brazil 10 <1%
India 9 <1%
Germany 8 <1%
France 6 <1%
Spain 6 <1%
Mexico 6 <1%
Canada 5 <1%
Other 68 2%
Unknown 3453 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 848 24%
Student > Bachelor 668 19%
Student > Master 664 18%
Researcher 449 12%
Student > Doctoral Student 194 5%
Other 427 12%
Unknown 353 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 1400 39%
Biochemistry, Genetics and Molecular Biology 966 27%
Medicine and Dentistry 211 6%
Immunology and Microbiology 130 4%
Neuroscience 76 2%
Other 369 10%
Unknown 451 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 29. 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 August 2020.
All research outputs
#831,472
of 17,462,542 outputs
Outputs from BMC Bioinformatics
#101
of 6,171 outputs
Outputs of similar age
#5,177
of 133,087 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 8 outputs
Altmetric has tracked 17,462,542 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,171 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done particularly well, scoring higher than 98% 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 133,087 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 96% of its contemporaries.
We're also able to compare this research output to 8 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