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Mendeley readers
Attention Score in Context
| Title |
Infection and genotype remodel the entire soybean transcriptome
|
|---|---|
| Published in |
BMC Genomics, January 2009
|
| DOI | 10.1186/1471-2164-10-49 |
| Pubmed ID | |
| Authors |
Lecong Zhou, Santiago X Mideros, Lei Bao, Regina Hanlon, Felipe D Arredondo, Sucheta Tripathy, Konstantinos Krampis, Adam Jerauld, Clive Evans, Steven K St Martin, MA Saghai Maroof, Ina Hoeschele, Anne E Dorrance, Brett M Tyler |
| Abstract |
High throughput methods, such as high density oligonucleotide microarray measurements of mRNA levels, are popular and critical to genome scale analysis and systems biology. However understanding the results of these analyses and in particular understanding the very wide range of levels of transcriptional changes observed is still a significant challenge. Many researchers still use an arbitrary cut off such as two-fold in order to identify changes that may be biologically significant. We have used a very large-scale microarray experiment involving 72 biological replicates to analyze the response of soybean plants to infection by the pathogen Phytophthora sojae and to analyze transcriptional modulation as a result of genotypic variation. |
Mendeley readers
The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 4% |
| Italy | 1 | 2% |
| Brazil | 1 | 2% |
| Australia | 1 | 2% |
| Singapore | 1 | 2% |
| United Kingdom | 1 | 2% |
| Unknown | 50 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 20 | 35% |
| Student > Ph. D. Student | 9 | 16% |
| Student > Master | 9 | 16% |
| Professor > Associate Professor | 7 | 12% |
| Student > Bachelor | 3 | 5% |
| Other | 6 | 11% |
| Unknown | 3 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 44 | 77% |
| Biochemistry, Genetics and Molecular Biology | 4 | 7% |
| Computer Science | 2 | 4% |
| Engineering | 2 | 4% |
| Physics and Astronomy | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 3 | 5% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 25 May 2010.
All research outputs
#12,846,160
of 22,649,029 outputs
Outputs from BMC Genomics
#4,546
of 10,605 outputs
Outputs of similar age
#137,242
of 170,154 outputs
Outputs of similar age from BMC Genomics
#105
of 122 outputs
Altmetric has tracked 22,649,029 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,605 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 55% 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 170,154 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 122 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.