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Open access resources for genome-wide association mapping in rice

Overview of attention for article published in Nature Communications, February 2016
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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 (94th percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
26 X users

Citations

dimensions_citation
394 Dimensions

Readers on

mendeley
434 Mendeley
citeulike
2 CiteULike
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Title
Open access resources for genome-wide association mapping in rice
Published in
Nature Communications, February 2016
DOI 10.1038/ncomms10532
Pubmed ID
Authors

Susan R. McCouch, Mark H. Wright, Chih-Wei Tung, Lyza G. Maron, Kenneth L. McNally, Melissa Fitzgerald, Namrata Singh, Genevieve DeClerck, Francisco Agosto-Perez, Pavel Korniliev, Anthony J. Greenberg, Ma. Elizabeth B. Naredo, Sheila Mae Q. Mercado, Sandra E. Harrington, Yuxin Shi, Darcy A. Branchini, Paula R. Kuser-Falcão, Hei Leung, Kowaru Ebana, Masahiro Yano, Georgia Eizenga, Anna McClung, Jason Mezey

Abstract

Increasing food production is essential to meet the demands of a growing human population, with its rising income levels and nutritional expectations. To address the demand, plant breeders seek new sources of genetic variation to enhance the productivity, sustainability and resilience of crop varieties. Here we launch a high-resolution, open-access research platform to facilitate genome-wide association mapping in rice, a staple food crop. The platform provides an immortal collection of diverse germplasm, a high-density single-nucleotide polymorphism data set tailored for gene discovery, well-documented analytical strategies, and a suite of bioinformatics resources to facilitate biological interpretation. Using grain length, we demonstrate the power and resolution of our new high-density rice array, the accompanying genotypic data set, and an expanded diversity panel for detecting major and minor effect QTLs and subpopulation-specific alleles, with immediate implications for rice improvement.

X Demographics

X Demographics

The data shown below were collected from the profiles of 26 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 434 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 <1%
France 2 <1%
Netherlands 1 <1%
Malaysia 1 <1%
United Kingdom 1 <1%
Israel 1 <1%
Benin 1 <1%
Philippines 1 <1%
Unknown 422 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 91 21%
Student > Ph. D. Student 84 19%
Student > Master 42 10%
Student > Bachelor 32 7%
Student > Doctoral Student 31 7%
Other 46 11%
Unknown 108 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 239 55%
Biochemistry, Genetics and Molecular Biology 50 12%
Computer Science 8 2%
Psychology 6 1%
Environmental Science 3 <1%
Other 15 3%
Unknown 113 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 32. 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 23 May 2017.
All research outputs
#1,196,014
of 24,701,594 outputs
Outputs from Nature Communications
#18,311
of 53,563 outputs
Outputs of similar age
#21,813
of 407,332 outputs
Outputs of similar age from Nature Communications
#262
of 753 outputs
Altmetric has tracked 24,701,594 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 53,563 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 56.0. This one has gotten more attention than average, scoring higher than 65% 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 407,332 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 94% of its contemporaries.
We're also able to compare this research output to 753 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.