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Mendeley readers
Attention Score in Context
| Title |
A quantitative RT-PCR platform for high-throughput expression profiling of 2500 rice transcription factors
|
|---|---|
| Published in |
Plant Methods, June 2007
|
| DOI | 10.1186/1746-4811-3-7 |
| Pubmed ID | |
| Authors |
Camila Caldana, Wolf-Rüdiger Scheible, Bernd Mueller-Roeber, Slobodan Ruzicic |
| Abstract |
Quantitative reverse transcription - polymerase chain reaction (qRT-PCR) has been demonstrated to be particularly suitable for the analysis of weakly expressed genes, such as those encoding transcription factors. Rice (Oryza sativa L.) is an important crop and the most advanced model for monocotyledonous species; its nuclear genome has been sequenced and molecular tools are being developed for functional analyses. However, high-throughput methods for rice research are still limited and a large-scale qRT-PCR platform for gene expression analyses has not been reported. |
Mendeley readers
The data shown below were compiled from readership statistics for 210 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| South Africa | 3 | 1% |
| Canada | 3 | 1% |
| Brazil | 2 | <1% |
| United States | 2 | <1% |
| India | 2 | <1% |
| Italy | 1 | <1% |
| Sweden | 1 | <1% |
| Norway | 1 | <1% |
| France | 1 | <1% |
| Other | 7 | 3% |
| Unknown | 187 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 58 | 28% |
| Researcher | 33 | 16% |
| Student > Master | 30 | 14% |
| Professor > Associate Professor | 16 | 8% |
| Student > Doctoral Student | 15 | 7% |
| Other | 35 | 17% |
| Unknown | 23 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 128 | 61% |
| Biochemistry, Genetics and Molecular Biology | 34 | 16% |
| Computer Science | 2 | <1% |
| Engineering | 2 | <1% |
| Earth and Planetary Sciences | 1 | <1% |
| Other | 10 | 5% |
| Unknown | 33 | 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 18 July 2014.
All research outputs
#20,233,066
of 22,758,963 outputs
Outputs from Plant Methods
#1,048
of 1,080 outputs
Outputs of similar age
#67,969
of 70,395 outputs
Outputs of similar age from Plant Methods
#1
of 1 outputs
Altmetric has tracked 22,758,963 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 1,080 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. 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 70,395 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 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them