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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Identification and characterization of transcript polymorphisms in soybean lines varying in oil composition and content
|
|---|---|
| Published in |
BMC Genomics, April 2014
|
| DOI | 10.1186/1471-2164-15-299 |
| Pubmed ID | |
| Authors |
Wolfgang Goettel, Eric Xia, Robert Upchurch, Ming-Li Wang, Pengyin Chen, Yong-Qiang Charles An |
| Abstract |
Variation in seed oil composition and content among soybean varieties is largely attributed to differences in transcript sequences and/or transcript accumulation of oil production related genes in seeds. Discovery and analysis of sequence and expression variations in these genes will accelerate soybean oil quality improvement. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 33% |
| Germany | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Malaysia | 1 | 2% |
| Madagascar | 1 | 2% |
| Brazil | 1 | 2% |
| Unknown | 41 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 20% |
| Student > Master | 7 | 16% |
| Researcher | 7 | 16% |
| Professor > Associate Professor | 5 | 11% |
| Student > Doctoral Student | 2 | 5% |
| Other | 4 | 9% |
| Unknown | 10 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 18 | 41% |
| Biochemistry, Genetics and Molecular Biology | 8 | 18% |
| Computer Science | 3 | 7% |
| Medicine and Dentistry | 2 | 5% |
| Unknown | 13 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 03 December 2014.
All research outputs
#14,195,272
of 22,754,104 outputs
Outputs from BMC Genomics
#5,689
of 10,636 outputs
Outputs of similar age
#120,332
of 227,083 outputs
Outputs of similar age from BMC Genomics
#79
of 180 outputs
Altmetric has tracked 22,754,104 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,636 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 42nd percentile – i.e., 42% 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 227,083 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 180 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.