You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
atBioNet– an integrated network analysis tool for genomics and biomarker discovery
|
|---|---|
| Published in |
BMC Genomics, July 2012
|
| DOI | 10.1186/1471-2164-13-325 |
| Pubmed ID | |
| Authors |
Yijun Ding, Minjun Chen, Zhichao Liu, Don Ding, Yanbin Ye, Min Zhang, Reagan Kelly, Li Guo, Zhenqiang Su, Stephen C Harris, Feng Qian, Weigong Ge, Hong Fang, Xiaowei Xu, Weida Tong |
| Abstract |
Large amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. |
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 % |
|---|---|---|
| Unknown | 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 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Hungary | 1 | 2% |
| Germany | 1 | 2% |
| France | 1 | 2% |
| Mexico | 1 | 2% |
| United States | 1 | 2% |
| Unknown | 56 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 23% |
| Researcher | 14 | 23% |
| Student > Bachelor | 6 | 10% |
| Student > Postgraduate | 4 | 7% |
| Professor > Associate Professor | 4 | 7% |
| Other | 14 | 23% |
| Unknown | 5 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 21 | 34% |
| Computer Science | 9 | 15% |
| Biochemistry, Genetics and Molecular Biology | 8 | 13% |
| Medicine and Dentistry | 6 | 10% |
| Engineering | 4 | 7% |
| Other | 6 | 10% |
| Unknown | 7 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 August 2012.
All research outputs
#3,148,995
of 22,671,366 outputs
Outputs from BMC Genomics
#1,200
of 10,614 outputs
Outputs of similar age
#21,734
of 163,875 outputs
Outputs of similar age from BMC Genomics
#11
of 118 outputs
Altmetric has tracked 22,671,366 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,614 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 88% 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 163,875 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 118 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.