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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A systems biology approach toward understanding seed composition in soybean
|
|---|---|
| Published in |
BMC Genomics, January 2015
|
| DOI | 10.1186/1471-2164-16-s3-s9 |
| Pubmed ID | |
| Authors |
Ling Li, Manhoi Hur, Joon-Yong Lee, Wenxu Zhou, Zhihong Song, Nick Ransom, Cumhur Yusuf Demirkale, Dan Nettleton, Mark Westgate, Zebulun Arendsee, Vidya Iyer, Jackie Shanks, Basil Nikolau, Eve Syrkin Wurtele |
| Abstract |
The molecular, biochemical, and genetic mechanisms that regulate the complex metabolic network of soybean seed development determine the ultimate balance of protein, lipid, and carbohydrate stored in the mature seed. Many of the genes and metabolites that participate in seed metabolism are unknown or poorly defined; even more remains to be understood about the regulation of their metabolic networks. A global omics analysis can provide insights into the regulation of seed metabolism, even without a priori assumptions about the structure of these networks. |
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 % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 1% |
| Slovakia | 1 | 1% |
| Brazil | 1 | 1% |
| Unknown | 86 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 28 | 31% |
| Researcher | 24 | 27% |
| Student > Master | 7 | 8% |
| Student > Doctoral Student | 3 | 3% |
| Professor > Associate Professor | 3 | 3% |
| Other | 9 | 10% |
| Unknown | 15 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 44 | 49% |
| Biochemistry, Genetics and Molecular Biology | 11 | 12% |
| Engineering | 4 | 4% |
| Computer Science | 2 | 2% |
| Social Sciences | 2 | 2% |
| Other | 7 | 8% |
| Unknown | 19 | 21% |
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 26 September 2015.
All research outputs
#20,262,276
of 22,792,160 outputs
Outputs from BMC Genomics
#9,273
of 10,648 outputs
Outputs of similar age
#297,286
of 353,610 outputs
Outputs of similar age from BMC Genomics
#238
of 265 outputs
Altmetric has tracked 22,792,160 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 10,648 research outputs from this source. They receive a mean Attention Score of 4.7. 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 353,610 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 265 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.