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Attention Score in Context
Title |
Combining SNP discovery from next-generation sequencing data with bulked segregant analysis (BSA) to fine-map genes in polyploid wheat
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Published in |
BMC Plant Biology, January 2012
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DOI | 10.1186/1471-2229-12-14 |
Pubmed ID | |
Authors |
Martin Trick, Nikolai Maria Adamski, Sarah G Mugford, Cong-Cong Jiang, Melanie Febrer, Cristobal Uauy |
Abstract |
Next generation sequencing (NGS) technologies are providing new ways to accelerate fine-mapping and gene isolation in many species. To date, the majority of these efforts have focused on diploid organisms with readily available whole genome sequence information. In this study, as a proof of concept, we tested the use of NGS for SNP discovery in tetraploid wheat lines differing for the previously cloned grain protein content (GPC) gene GPC-B1. Bulked segregant analysis (BSA) was used to define a subset of putative SNPs within the candidate gene region, which were then used to fine-map GPC-B1. |
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.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 50% |
Chile | 1 | 25% |
Unknown | 1 | 25% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 75% |
Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 391 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 5 | 1% |
China | 4 | 1% |
Argentina | 3 | <1% |
France | 2 | <1% |
Italy | 2 | <1% |
Sweden | 2 | <1% |
Brazil | 2 | <1% |
India | 2 | <1% |
Japan | 2 | <1% |
Other | 11 | 3% |
Unknown | 356 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 111 | 28% |
Student > Ph. D. Student | 110 | 28% |
Student > Master | 50 | 13% |
Student > Bachelor | 15 | 4% |
Student > Postgraduate | 15 | 4% |
Other | 51 | 13% |
Unknown | 39 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 283 | 72% |
Biochemistry, Genetics and Molecular Biology | 38 | 10% |
Computer Science | 7 | 2% |
Environmental Science | 5 | 1% |
Engineering | 4 | 1% |
Other | 10 | 3% |
Unknown | 44 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 April 2012.
All research outputs
#1,938,465
of 22,662,201 outputs
Outputs from BMC Plant Biology
#86
of 3,205 outputs
Outputs of similar age
#15,608
of 246,248 outputs
Outputs of similar age from BMC Plant Biology
#2
of 44 outputs
Altmetric has tracked 22,662,201 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 3,205 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done particularly well, scoring higher than 97% 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 246,248 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 93% of its contemporaries.
We're also able to compare this research output to 44 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 95% of its contemporaries.