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Mendeley readers
Attention Score in Context
| Title |
Identification of genome-wide single nucleotide polymorphisms in allopolyploid crop Brassica napus
|
|---|---|
| Published in |
BMC Genomics, October 2013
|
| DOI | 10.1186/1471-2164-14-717 |
| Pubmed ID | |
| Authors |
Shunmou Huang, Linbin Deng, Mei Guan, Jiana Li, Kun Lu, Hanzhong Wang, Donghui Fu, Annaliese S Mason, Shengyi Liu, Wei Hua |
| Abstract |
Single nucleotide polymorphisms (SNPs) are the most common type of genetic variation. Identification of large numbers of SNPs is helpful for genetic diversity analysis, map-based cloning, genome-wide association analyses and marker-assisted breeding. Recently, identifying genome-wide SNPs in allopolyploid Brassica napus (rapeseed, canola) by resequencing many accessions has become feasible, due to the availability of reference genomes of Brassica rapa (2n = AA) and Brassica oleracea (2n = CC), which are the progenitor species of B. napus (2n = AACC). Although many SNPs in B. napus have been released, the objective in the present study was to produce a larger, more informative set of SNPs for large-scale and efficient genotypic screening. Hence, short-read genome sequencing was conducted on ten elite B. napus accessions for SNP discovery. A subset of these SNPs was randomly selected for sequence validation and for genotyping efficiency testing using the Illumina GoldenGate assay. |
Mendeley readers
The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 79 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 20 | 25% |
| Researcher | 19 | 24% |
| Student > Master | 8 | 10% |
| Student > Bachelor | 5 | 6% |
| Professor > Associate Professor | 5 | 6% |
| Other | 8 | 10% |
| Unknown | 14 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 49 | 62% |
| Biochemistry, Genetics and Molecular Biology | 9 | 11% |
| Computer Science | 2 | 3% |
| Unspecified | 1 | 1% |
| Engineering | 1 | 1% |
| Other | 0 | 0% |
| Unknown | 17 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 20 October 2013.
All research outputs
#6,741,701
of 25,374,917 outputs
Outputs from BMC Genomics
#2,635
of 11,244 outputs
Outputs of similar age
#56,773
of 224,568 outputs
Outputs of similar age from BMC Genomics
#37
of 212 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 76% 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 224,568 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 212 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.