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GMATA: An Integrated Software Package for Genome-Scale SSR Mining, Marker Development and Viewing

Overview of attention for article published in Frontiers in Plant Science, September 2016
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  • 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 (96th percentile)

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2 news outlets
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1 X user

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190 Dimensions

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127 Mendeley
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Title
GMATA: An Integrated Software Package for Genome-Scale SSR Mining, Marker Development and Viewing
Published in
Frontiers in Plant Science, September 2016
DOI 10.3389/fpls.2016.01350
Pubmed ID
Authors

Xuewen Wang, Le Wang

Abstract

Simple sequence repeats (SSRs), also referred to as microsatellites, are highly variable tandem DNAs that are widely used as genetic markers. The increasing availability of whole-genome and transcript sequences provides information resources for SSR marker development. However, efficient software is required to efficiently identify and display SSR information along with other gene features at a genome scale. We developed novel software package Genome-wide Microsatellite Analyzing Tool Package (GMATA) integrating SSR mining, statistical analysis and plotting, marker design, polymorphism screening and marker transferability, and enabled simultaneously display SSR markers with other genome features. GMATA applies novel strategies for SSR analysis and primer design in large genomes, which allows GMATA to perform faster calculation and provides more accurate results than existing tools. Our package is also capable of processing DNA sequences of any size on a standard computer. GMATA is user friendly, only requires mouse clicks or types inputs on the command line, and is executable in multiple computing platforms. We demonstrated the application of GMATA in plants genomes and reveal a novel distribution pattern of SSRs in 15 grass genomes. The most abundant motifs are dimer GA/TC, the A/T monomer and the GCG/CGC trimer, rather than the rich G/C content in DNA sequence. We also revealed that SSR count is a linear to the chromosome length in fully assembled grass genomes. GMATA represents a powerful application tool that facilitates genomic sequence analyses. GAMTA is freely available at http://sourceforge.net/projects/gmata/?source=navbar.

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 readers

Mendeley readers

The data shown below were compiled from readership statistics for 127 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 127 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 20%
Researcher 21 17%
Student > Bachelor 13 10%
Student > Postgraduate 5 4%
Professor 4 3%
Other 15 12%
Unknown 44 35%
Readers by discipline Count As %
Agricultural and Biological Sciences 39 31%
Biochemistry, Genetics and Molecular Biology 21 17%
Engineering 4 3%
Computer Science 3 2%
Social Sciences 2 2%
Other 8 6%
Unknown 50 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 19 September 2016.
All research outputs
#2,088,971
of 25,374,647 outputs
Outputs from Frontiers in Plant Science
#780
of 24,598 outputs
Outputs of similar age
#35,127
of 330,899 outputs
Outputs of similar age from Frontiers in Plant Science
#13
of 447 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 24,598 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done particularly well, scoring higher than 96% 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 330,899 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 447 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.