You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
Title |
Mapping dynamic QTL for plant height in triticale
|
---|---|
Published in |
BMC Genomic Data, May 2014
|
DOI | 10.1186/1471-2156-15-59 |
Pubmed ID | |
Authors |
Tobias Würschum, Wenxin Liu, Lucas Busemeyer, Matthew R Tucker, Jochen C Reif, Elmar A Weissmann, Volker Hahn, Arno Ruckelshausen, Hans Peter Maurer |
Abstract |
Plant height is a prime example of a dynamic trait that changes constantly throughout adult development. In this study we utilised a large triticale mapping population, comprising 647 doubled haploid lines derived from 4 families, to phenotype for plant height by a precision phenotyping platform at multiple time points. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 37 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 11 | 30% |
Researcher | 10 | 27% |
Student > Ph. D. Student | 5 | 14% |
Student > Bachelor | 2 | 5% |
Student > Doctoral Student | 1 | 3% |
Other | 2 | 5% |
Unknown | 6 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 23 | 62% |
Biochemistry, Genetics and Molecular Biology | 3 | 8% |
Computer Science | 2 | 5% |
Engineering | 2 | 5% |
Energy | 1 | 3% |
Other | 0 | 0% |
Unknown | 6 | 16% |
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 19 May 2014.
All research outputs
#22,756,649
of 25,371,288 outputs
Outputs from BMC Genomic Data
#1,008
of 1,204 outputs
Outputs of similar age
#208,184
of 240,993 outputs
Outputs of similar age from BMC Genomic Data
#26
of 30 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,204 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 1st percentile – i.e., 1% 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 240,993 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.