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X Demographics
Mendeley readers
Attention Score in Context
| Title |
solGS: a web-based tool for genomic selection
|
|---|---|
| Published in |
BMC Bioinformatics, December 2014
|
| DOI | 10.1186/s12859-014-0398-7 |
| Pubmed ID | |
| Authors |
Isaak Y Tecle, Jeremy D Edwards, Naama Menda, Chiedozie Egesi, Ismail Y Rabbi, Peter Kulakow, Robert Kawuki, Jean-Luc Jannink, Lukas A Mueller |
| Abstract |
Genomic selection (GS) promises to improve accuracy in estimating breeding values and genetic gain for quantitative traits compared to traditional breeding methods. Its reliance on high-throughput genome-wide markers and statistical complexity, however, is a serious challenge in data management, analysis, and sharing. A bioinformatics infrastructure for data storage and access, and user-friendly web-based tool for analysis and sharing output is needed to make GS more practical for breeders. |
X Demographics
The data shown below were collected from the profiles of 7 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 States | 3 | 43% |
| India | 1 | 14% |
| Norway | 1 | 14% |
| Unknown | 2 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 57% |
| Scientists | 3 | 43% |
Mendeley readers
The data shown below were compiled from readership statistics for 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 1% |
| Brazil | 1 | 1% |
| Benin | 1 | 1% |
| Korea, Republic of | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 81 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 28 | 33% |
| Student > Ph. D. Student | 13 | 15% |
| Student > Master | 8 | 9% |
| Student > Postgraduate | 6 | 7% |
| Student > Bachelor | 5 | 6% |
| Other | 12 | 14% |
| Unknown | 14 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 48 | 56% |
| Computer Science | 7 | 8% |
| Biochemistry, Genetics and Molecular Biology | 3 | 3% |
| Engineering | 2 | 2% |
| Veterinary Science and Veterinary Medicine | 1 | 1% |
| Other | 3 | 3% |
| Unknown | 22 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 13 January 2015.
All research outputs
#2,163,505
of 22,774,233 outputs
Outputs from BMC Bioinformatics
#585
of 7,276 outputs
Outputs of similar age
#31,871
of 354,985 outputs
Outputs of similar age from BMC Bioinformatics
#13
of 152 outputs
Altmetric has tracked 22,774,233 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,276 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 91% 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 354,985 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 91% of its contemporaries.
We're also able to compare this research output to 152 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 90% of its contemporaries.