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QTL Mapping and Data Mining to Identify Genes Associated With the Sinorhizobium fredii HH103 T3SS Effector NopD in Soybean

Overview of attention for article published in Frontiers in Plant Science, May 2020
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

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4 X users

Citations

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22 Dimensions

Readers on

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24 Mendeley
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Title
QTL Mapping and Data Mining to Identify Genes Associated With the Sinorhizobium fredii HH103 T3SS Effector NopD in Soybean
Published in
Frontiers in Plant Science, May 2020
DOI 10.3389/fpls.2020.00453
Pubmed ID
Authors

Jinhui Wang, Jieqi Wang, Chao Ma, Ziqi Zhou, Decheng Yang, Junzan Zheng, Qi Wang, Huiwen Li, Hongyang Zhou, Zhijun Sun, Hanxi Liu, Jianyi Li, Lin Chen, Qinglin Kang, Zhaoming Qi, Hongwei Jiang, Rongsheng Zhu, Xiaoxia Wu, Chunyan Liu, Qingshan Chen, Dawei Xin

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 13%
Student > Ph. D. Student 3 13%
Researcher 3 13%
Student > Master 2 8%
Professor 1 4%
Other 2 8%
Unknown 10 42%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 25%
Agricultural and Biological Sciences 6 25%
Unspecified 1 4%
Engineering 1 4%
Unknown 10 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 25 June 2020.
All research outputs
#14,646,643
of 25,163,238 outputs
Outputs from Frontiers in Plant Science
#6,837
of 24,162 outputs
Outputs of similar age
#196,207
of 395,996 outputs
Outputs of similar age from Frontiers in Plant Science
#238
of 529 outputs
Altmetric has tracked 25,163,238 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 24,162 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 70% 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 395,996 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 529 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 54% of its contemporaries.