| Title |
Discovering hidden relationships between renal diseases and regulated genes through 3D network visualizations
|
|---|---|
| Published in |
BMC Research Notes, November 2010
|
| DOI | 10.1186/1756-0500-3-296 |
| Pubmed ID | |
| Authors |
Suresh K Bhavnani, Arunkumaar Ganesan, Theodore Hall, Eric Maslowski, Felix Eichinger, Sebastian Martini, Paul Saxman, Gowtham Bellala, Matthias Kretzler |
| Abstract |
In a recent study, two-dimensional (2D) network layouts were used to visualize and quantitatively analyze the relationship between chronic renal diseases and regulated genes. The results revealed complex relationships between disease type, gene specificity, and gene regulation type, which led to important insights about the underlying biological pathways. Here we describe an attempt to extend our understanding of these complex relationships by reanalyzing the data using three-dimensional (3D) network layouts, displayed through 2D and 3D viewing methods. |
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 % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 6% |
| Luxembourg | 1 | 6% |
| Unknown | 16 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 4 | 22% |
| Student > Ph. D. Student | 4 | 22% |
| Researcher | 3 | 17% |
| Student > Bachelor | 1 | 6% |
| Student > Master | 1 | 6% |
| Other | 3 | 17% |
| Unknown | 2 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 33% |
| Medicine and Dentistry | 4 | 22% |
| Computer Science | 3 | 17% |
| Mathematics | 1 | 6% |
| Psychology | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 2 | 11% |
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 10 March 2022.
All research outputs
#7,404,945
of 23,305,591 outputs
Outputs from BMC Research Notes
#1,187
of 4,304 outputs
Outputs of similar age
#35,845
of 102,186 outputs
Outputs of similar age from BMC Research Notes
#11
of 32 outputs
Altmetric has tracked 23,305,591 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 4,304 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one has gotten more attention than average, scoring higher than 71% 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 102,186 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 64% of its contemporaries.
We're also able to compare this research output to 32 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 62% of its contemporaries.