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Mendeley readers
Attention Score in Context
| Title |
Genome-wide transcriptional analysis of two soybean genotypes under dehydration and rehydration conditions
|
|---|---|
| Published in |
BMC Genomics, October 2013
|
| DOI | 10.1186/1471-2164-14-687 |
| Pubmed ID | |
| Authors |
Li M Chen, Xin A Zhou, Wen B Li, Wei Chang, Rong Zhou, Cheng Wang, Ai H Sha, Zhi H Shan, Chan J Zhang, De Z Qiu, Zhong L Yang, Shui L Chen |
| Abstract |
Soybean is an important crop that provides valuable proteins and oils for human use. Because soybean growth and development is extremely sensitive to water deficit, quality and crop yields are severely impacted by drought stress. In the face of limited water resources, drought-responsive genes are therefore of interest. Identification and analysis of dehydration- and rehydration-inducible differentially expressed genes (DEGs) would not only aid elucidation of molecular mechanisms of stress response, but also enable improvement of crop stress tolerance via gene transfer. Using Digital Gene Expression Tag profiling (DGE), a new technique based on Illumina sequencing, we analyzed expression profiles between two soybean genotypes to identify drought-responsive genes. |
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 % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 1% |
| United Kingdom | 1 | 1% |
| Paraguay | 1 | 1% |
| Brazil | 1 | 1% |
| Unknown | 68 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 22% |
| Student > Master | 15 | 21% |
| Student > Ph. D. Student | 13 | 18% |
| Student > Doctoral Student | 4 | 6% |
| Professor | 3 | 4% |
| Other | 6 | 8% |
| Unknown | 15 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 42 | 58% |
| Biochemistry, Genetics and Molecular Biology | 9 | 13% |
| Psychology | 2 | 3% |
| Computer Science | 1 | 1% |
| Neuroscience | 1 | 1% |
| Other | 0 | 0% |
| Unknown | 17 | 24% |
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 23 October 2013.
All research outputs
#18,351,676
of 22,727,570 outputs
Outputs from BMC Genomics
#8,158
of 10,628 outputs
Outputs of similar age
#155,406
of 208,531 outputs
Outputs of similar age from BMC Genomics
#91
of 148 outputs
Altmetric has tracked 22,727,570 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,628 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% 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 208,531 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 148 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.