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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Enabling dynamic network analysis through visualization in TVNViewer
|
|---|---|
| Published in |
BMC Bioinformatics, August 2012
|
| DOI | 10.1186/1471-2105-13-204 |
| Pubmed ID | |
| Authors |
Ross E Curtis, Jing Xiang, Ankur Parikh, Peter Kinnaird, Eric P Xing |
| Abstract |
Many biological processes are context-dependent or temporally specific. As a result, relationships between molecular constituents evolve across time and environments. While cutting-edge machine learning techniques can recover these networks, exploring and interpreting the rewiring behavior is challenging. Information visualization shines in this type of exploratory analysis, motivating the development ofTVNViewer (http://sailing.cs.cmu.edu/tvnviewer), a visualization tool for dynamic network analysis. |
X Demographics
The data shown below were collected from the profiles of 2 X users 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 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 6% |
| Canada | 1 | 2% |
| Brazil | 1 | 2% |
| China | 1 | 2% |
| Belgium | 1 | 2% |
| Unknown | 42 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 24% |
| Student > Ph. D. Student | 10 | 20% |
| Student > Master | 6 | 12% |
| Professor > Associate Professor | 4 | 8% |
| Other | 4 | 8% |
| Other | 8 | 16% |
| Unknown | 5 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 13 | 27% |
| Agricultural and Biological Sciences | 9 | 18% |
| Medicine and Dentistry | 5 | 10% |
| Environmental Science | 4 | 8% |
| Biochemistry, Genetics and Molecular Biology | 3 | 6% |
| Other | 6 | 12% |
| Unknown | 9 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 17 September 2012.
All research outputs
#14,151,132
of 22,678,224 outputs
Outputs from BMC Bioinformatics
#4,711
of 7,251 outputs
Outputs of similar age
#87,612
of 149,515 outputs
Outputs of similar age from BMC Bioinformatics
#54
of 101 outputs
Altmetric has tracked 22,678,224 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,251 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 30th percentile – i.e., 30% 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 149,515 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 101 others from the same source and published within six weeks on either side of this one. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.