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Mendeley readers
Attention Score in Context
| Title |
Systems biology approach to identify transcriptome reprogramming and candidate microRNA targets during the progression of polycystic kidney disease
|
|---|---|
| Published in |
BMC Systems Biology, April 2011
|
| DOI | 10.1186/1752-0509-5-56 |
| Pubmed ID | |
| Authors |
Priyanka Pandey, Shan Qin, Jacqueline Ho, Jing Zhou, Jordan A Kreidberg |
| Abstract |
Autosomal dominant polycystic kidney disease (ADPKD) is characterized by cyst formation throughout the kidney parenchyma. It is caused by mutations in either of two genes, PKD1 and PKD2. Mice that lack functional Pkd1 (Pkd1⁻/⁻), develop rapidly progressive cystic disease during embryogenesis, and serve as a model to study human ADPKD. Genome wide transcriptome reprogramming and the possible roles of micro-RNAs (miRNAs) that affect the initiation and progression of cyst formation in the Pkd1⁻/⁻ have yet to be studied. miRNAs are small, regulatory non-coding RNAs, implicated in a wide spectrum of biological processes. Their expression levels are altered in several diseases including kidney cancer, diabetic nephropathy and PKD. |
Mendeley readers
The data shown below were compiled from readership statistics for 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 2 | 2% |
| Chile | 1 | 1% |
| France | 1 | 1% |
| Germany | 1 | 1% |
| Canada | 1 | 1% |
| United Kingdom | 1 | 1% |
| Iran, Islamic Republic of | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 89 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 20 | 20% |
| Researcher | 18 | 18% |
| Other | 8 | 8% |
| Student > Master | 8 | 8% |
| Professor | 6 | 6% |
| Other | 21 | 21% |
| Unknown | 17 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 32 | 33% |
| Medicine and Dentistry | 15 | 15% |
| Biochemistry, Genetics and Molecular Biology | 12 | 12% |
| Engineering | 4 | 4% |
| Computer Science | 2 | 2% |
| Other | 13 | 13% |
| Unknown | 20 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 11 June 2015.
All research outputs
#6,392,214
of 22,710,079 outputs
Outputs from BMC Systems Biology
#232
of 1,142 outputs
Outputs of similar age
#34,779
of 109,751 outputs
Outputs of similar age from BMC Systems Biology
#5
of 14 outputs
Altmetric has tracked 22,710,079 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done well, scoring higher than 78% 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 109,751 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.