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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Accurate multiple network alignment through context-sensitive random walk
|
|---|---|
| Published in |
BMC Systems Biology, January 2015
|
| DOI | 10.1186/1752-0509-9-s1-s7 |
| Pubmed ID | |
| Authors |
Hyundoo Jeong, Byung-Jun Yoon |
| Abstract |
Comparative network analysis can provide an effective means of analyzing large-scale biological networks and gaining novel insights into their structure and organization. Global network alignment aims to predict the best overall mapping between a given set of biological networks, thereby identifying important similarities as well as differences among the networks. It has been shown that network alignment methods can be used to detect pathways or network modules that are conserved across different networks. Until now, a number of network alignment algorithms have been proposed based on different formulations and approaches, many of them focusing on pairwise alignment. |
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 % |
|---|---|---|
| Netherlands | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
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 % |
|---|---|---|
| India | 1 | 5% |
| United States | 1 | 5% |
| Unknown | 19 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 29% |
| Researcher | 4 | 19% |
| Student > Master | 4 | 19% |
| Lecturer | 2 | 10% |
| Student > Bachelor | 1 | 5% |
| Other | 4 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 29% |
| Computer Science | 5 | 24% |
| Medicine and Dentistry | 3 | 14% |
| Biochemistry, Genetics and Molecular Biology | 2 | 10% |
| Environmental Science | 1 | 5% |
| Other | 3 | 14% |
| Unknown | 1 | 5% |
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 18 November 2015.
All research outputs
#16,048,318
of 25,374,917 outputs
Outputs from BMC Systems Biology
#556
of 1,132 outputs
Outputs of similar age
#200,005
of 359,552 outputs
Outputs of similar age from BMC Systems Biology
#15
of 42 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,132 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 46th percentile – i.e., 46% 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 359,552 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 42 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 57% of its contemporaries.