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Mendeley readers
Attention Score in Context
| Title |
Association Analysis in Rice: From Application to Utilization
|
|---|---|
| Published in |
Frontiers in Plant Science, August 2016
|
| DOI | 10.3389/fpls.2016.01202 |
| Pubmed ID | |
| Authors |
Peng Zhang, Kaizhen Zhong, Muhammad Qasim Shahid, Hanhua Tong |
| Abstract |
Association analysis based on linkage disequilibrium (LD) is an efficient way to dissect complex traits and to identify gene functions in rice. Although association analysis is an effective way to construct fine maps for quantitative traits, there are a few issues which need to be addressed. In this review, we will first summarize type, structure, and LD level of populations used for association analysis of rice, and then discuss the genotyping methods and statistical approaches used for association analysis in rice. Moreover, we will review current shortcomings and benefits of association analysis as well as specific types of future research to overcome these shortcomings. Furthermore, we will analyze the reasons for the underutilization of the results within association analysis in rice breeding. |
Mendeley readers
The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 1% |
| Unknown | 71 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 26 | 36% |
| Student > Ph. D. Student | 19 | 26% |
| Student > Master | 5 | 7% |
| Other | 4 | 6% |
| Student > Bachelor | 2 | 3% |
| Other | 8 | 11% |
| Unknown | 8 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 45 | 63% |
| Biochemistry, Genetics and Molecular Biology | 12 | 17% |
| Mathematics | 1 | 1% |
| Environmental Science | 1 | 1% |
| Computer Science | 1 | 1% |
| Other | 1 | 1% |
| Unknown | 11 | 15% |
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 12 January 2017.
All research outputs
#15,423,393
of 22,931,367 outputs
Outputs from Frontiers in Plant Science
#10,944
of 20,360 outputs
Outputs of similar age
#219,038
of 343,003 outputs
Outputs of similar age from Frontiers in Plant Science
#212
of 447 outputs
Altmetric has tracked 22,931,367 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 20,360 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 40th percentile – i.e., 40% 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 343,003 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
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 is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.