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X Demographics
Mendeley readers
Attention Score in Context
| Title |
SBGNViz: A Tool for Visualization and Complexity Management of SBGN Process Description Maps
|
|---|---|
| Published in |
PLOS ONE, June 2015
|
| DOI | 10.1371/journal.pone.0128985 |
| Pubmed ID | |
| Authors |
Mecit Sari, Istemi Bahceci, Ugur Dogrusoz, Selcuk Onur Sumer, Bülent Arman Aksoy, Özgün Babur, Emek Demir |
| Abstract |
Information about cellular processes and pathways is becoming increasingly available in detailed, computable standard formats such as BioPAX and SBGN. Effective visualization of this information is a key recurring requirement for biological data analysis, especially for -omic data. Biological data analysis is rapidly migrating to web based platforms; thus there is a substantial need for sophisticated web based pathway viewers that support these platforms and other use cases. Towards this goal, we developed a web based viewer named SBGNViz for process description maps in SBGN (SBGN-PD). SBGNViz can visualize both BioPAX and SBGN formats. Unique features of SBGNViz include the ability to nest nodes to arbitrary depths to represent molecular complexes and cellular locations, automatic pathway layout, editing and highlighting facilities to enable focus on sub-maps, and the ability to inspect pathway members for detailed information from EntrezGene. SBGNViz can be used within a web browser without any installation and can be readily embedded into web pages. SBGNViz has two editions built with ActionScript and JavaScript. The JavaScript edition, which also works on touch enabled devices, introduces novel methods for managing and reducing complexity of large SBGN-PD maps for more effective analysis. SBGNViz fills an important gap by making the large and fast-growing corpus of rich pathway information accessible to web based platforms. SBGNViz can be used in a variety of contexts and in multiple scenarios ranging from visualization of the results of a single study in a web page to building data analysis platforms. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Kyrgyzstan | 1 | 33% |
| United States | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 5% |
| United States | 1 | 5% |
| Unknown | 19 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 38% |
| Student > Master | 4 | 19% |
| Student > Doctoral Student | 2 | 10% |
| Student > Bachelor | 2 | 10% |
| Professor > Associate Professor | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 3 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 6 | 29% |
| Agricultural and Biological Sciences | 6 | 29% |
| Biochemistry, Genetics and Molecular Biology | 4 | 19% |
| Engineering | 2 | 10% |
| Unknown | 3 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 02 June 2015.
All research outputs
#13,202,980
of 22,808,725 outputs
Outputs from PLOS ONE
#104,410
of 194,660 outputs
Outputs of similar age
#123,365
of 267,542 outputs
Outputs of similar age from PLOS ONE
#3,151
of 6,833 outputs
Altmetric has tracked 22,808,725 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 194,660 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one is in the 45th percentile – i.e., 45% 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 267,542 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 53% of its contemporaries.
We're also able to compare this research output to 6,833 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 52% of its contemporaries.