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Mendeley readers
Attention Score in Context
| Title |
Refining transcriptional programs in kidney development by integration of deep RNA-sequencing and array-based spatial profiling
|
|---|---|
| Published in |
BMC Genomics, September 2011
|
| DOI | 10.1186/1471-2164-12-441 |
| Pubmed ID | |
| Authors |
Rathi D Thiagarajan, Nicole Cloonan, Brooke B Gardiner, Tim R Mercer, Gabriel Kolle, Ehsan Nourbakhsh, Shivangi Wani, Dave Tang, Keerthana Krishnan, Kylie M Georgas, Bree A Rumballe, Han S Chiu, Jason A Steen, John S Mattick, Melissa H Little, Sean M Grimmond |
| Abstract |
The developing mouse kidney is currently the best-characterized model of organogenesis at a transcriptional level. Detailed spatial maps have been generated for gene expression profiling combined with systematic in situ screening. These studies, however, fall short of capturing the transcriptional complexity arising from each locus due to the limited scope of microarray-based technology, which is largely based on "gene-centric" models. |
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 % |
|---|---|---|
| France | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 4% |
| Australia | 2 | 4% |
| Germany | 1 | 2% |
| Japan | 1 | 2% |
| United Kingdom | 1 | 2% |
| Unknown | 49 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 20 | 36% |
| Professor > Associate Professor | 8 | 14% |
| Student > Ph. D. Student | 8 | 14% |
| Professor | 6 | 11% |
| Student > Doctoral Student | 3 | 5% |
| Other | 6 | 11% |
| Unknown | 5 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 37 | 66% |
| Biochemistry, Genetics and Molecular Biology | 7 | 13% |
| Medicine and Dentistry | 4 | 7% |
| Social Sciences | 1 | 2% |
| Unknown | 7 | 13% |
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 05 September 2011.
All research outputs
#18,814,057
of 23,316,003 outputs
Outputs from BMC Genomics
#8,256
of 10,742 outputs
Outputs of similar age
#105,128
of 126,878 outputs
Outputs of similar age from BMC Genomics
#65
of 84 outputs
Altmetric has tracked 23,316,003 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 10,742 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 126,878 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 84 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.