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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Modularity analysis based on predicted protein-protein interactions provides new insights into pathogenicity and cellular process of Escherichia coli O157:H7
|
|---|---|
| Published in |
Theoretical Biology and Medical Modelling, December 2011
|
| DOI | 10.1186/1742-4682-8-47 |
| Pubmed ID | |
| Authors |
Xia Wang, Junjie Yue, Xianwen Ren, Yuelan Wang, Mingfeng Tan, Beiping LI, Long Liang |
| Abstract |
With the development of experimental techniques and bioinformatics, the quantity of data available from protein-protein interactions (PPIs) is increasing exponentially. Functional modules can be identified from protein interaction networks. It follows that the investigation of functional modules will generate a better understanding of cellular organization, processes, and functions. However, experimental PPI data are still limited, and no modularity analysis of PPIs in pathogens has been published to date. |
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 % |
|---|---|---|
| India | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 13 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 23% |
| Student > Bachelor | 3 | 23% |
| Lecturer | 1 | 8% |
| Student > Master | 1 | 8% |
| Researcher | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 4 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 46% |
| Computer Science | 1 | 8% |
| Immunology and Microbiology | 1 | 8% |
| Medicine and Dentistry | 1 | 8% |
| Chemistry | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 3 | 23% |
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 24 December 2011.
All research outputs
#14,141,940
of 22,660,862 outputs
Outputs from Theoretical Biology and Medical Modelling
#154
of 286 outputs
Outputs of similar age
#153,086
of 243,133 outputs
Outputs of similar age from Theoretical Biology and Medical Modelling
#3
of 4 outputs
Altmetric has tracked 22,660,862 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 286 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one is in the 43rd percentile – i.e., 43% 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 243,133 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one.