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SESAME (SEquence Sorter

Overview of attention for article published in Bioinformatics, November 2010
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103 Mendeley
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Article details
Title
SESAME (SEquence Sorter & AMplicon Explorer): genotyping based on high-throughput multiplex amplicon sequencing
Published in
Bioinformatics, November 2010
DOI 10.1093/bioinformatics/btq641
Pubmed ID
Authors
Abstract

Characterizing genetic diversity through genotyping short amplicons is central to evolutionary biology. Next-generation sequencing (NGS) technologies changed the scale at which these type of data are acquired. SESAME is a web application package that assists genotyping of multiplexed individuals for several markers based on NGS amplicon sequencing. It automatically assigns reads to loci and individuals, corrects reads if standard samples are available and provides an intuitive graphical user interface (GUI) for allele validation based on the sequences and associated decision-making tools. The aim of SESAME is to help allele identification among a large number of sequences.

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
Sweden 2 2%
France 2 2%
United States 1 <1%
Israel 1 <1%
Denmark 1 <1%
Germany 1 <1%
Czechia 1 <1%
China 1 <1%
Unknown 93 90%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 42 41%
Student > Ph. D. Student 18 17%
Student > Master 7 7%
Student > Doctoral Student 6 6%
Professor 6 6%
Other 17 17%
Unknown 7 7%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 62 60%
Biochemistry, Genetics and Molecular Biology 13 13%
Medicine and Dentistry 5 5%
Environmental Science 3 3%
Computer Science 3 3%
Other 6 6%
Unknown 11 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 2013.
All research outputs
#20,655,488
of 25,373,627 outputs
Outputs from Bioinformatics
#11,736
of 12,808 outputs
Outputs of similar age
#90,564
of 101,130 outputs
Outputs of similar age from Bioinformatics
#65
of 74 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 12,808 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 3rd percentile – i.e., 3% 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 101,130 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 74 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.