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Mendeley readers
Attention Score in Context
| Title |
Orthoscape: a cytoscape application for grouping and visualization KEGG based gene networks by taxonomy and homology principles
|
|---|---|
| Published in |
BMC Bioinformatics, January 2017
|
| DOI | 10.1186/s12859-016-1427-5 |
| Pubmed ID | |
| Authors |
Zakhar Sergeevich Mustafin, Sergey Alexandrovich Lashin, Yury Georgievich Matushkin, Konstantin Vladimirovich Gunbin, Dmitry Arkadievich Afonnikov |
| Abstract |
There are many available software tools for visualization and analysis of biological networks. Among them, Cytoscape ( http://cytoscape.org/ ) is one of the most comprehensive packages, with many plugins and applications which extends its functionality by providing analysis of protein-protein interaction, gene regulatory and gene co-expression networks, metabolic, signaling, neural as well as ecological-type networks including food webs, communities networks etc. Nevertheless, only three plugins tagged 'network evolution' found in Cytoscape official app store and in literature. We have developed a new Cytoscape 3.0 application Orthoscape aimed to facilitate evolutionary analysis of gene networks and visualize the results. Orthoscape aids in analysis of evolutionary information available for gene sets and networks by highlighting: (1) the orthology relationships between genes; (2) the evolutionary origin of gene network components; (3) the evolutionary pressure mode (diversifying or stabilizing, negative or positive selection) of orthologous groups in general and/or branch-oriented mode. The distinctive feature of Orthoscape is the ability to control all data analysis steps via user-friendly interface. Orthoscape allows its users to analyze gene networks or separated gene sets in the context of evolution. At each step of data analysis, Orthoscape also provides for convenient visualization and data manipulation. |
X Demographics
The data shown below were collected from the profiles of 4 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 | 2 | 50% |
| Japan | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 45 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 22% |
| Student > Bachelor | 5 | 11% |
| Student > Ph. D. Student | 5 | 11% |
| Professor > Associate Professor | 4 | 9% |
| Student > Doctoral Student | 4 | 9% |
| Other | 5 | 11% |
| Unknown | 12 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 13 | 29% |
| Biochemistry, Genetics and Molecular Biology | 8 | 18% |
| Computer Science | 4 | 9% |
| Psychology | 2 | 4% |
| Engineering | 2 | 4% |
| Other | 3 | 7% |
| Unknown | 13 | 29% |
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 28 July 2020.
All research outputs
#13,316,630
of 22,968,808 outputs
Outputs from BMC Bioinformatics
#4,021
of 7,306 outputs
Outputs of similar age
#205,853
of 419,234 outputs
Outputs of similar age from BMC Bioinformatics
#68
of 143 outputs
Altmetric has tracked 22,968,808 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 7,306 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 42nd percentile – i.e., 42% 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 419,234 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 50% of its contemporaries.
We're also able to compare this research output to 143 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 50% of its contemporaries.