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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Dynamic protein interaction modules in human hepatocellular carcinoma progression
|
|---|---|
| Published in |
BMC Systems Biology, December 2013
|
| DOI | 10.1186/1752-0509-7-s5-s2 |
| Pubmed ID | |
| Authors |
Hui Yu, Chen-Ching Lin, Yuan-Yuan Li, Zhongming Zhao |
| Abstract |
Gene expression profiles have been frequently integrated with the human protein interactome to uncover functional modules under specific conditions like disease state. Beyond traditional differential expression analysis, differential co-expression analysis has emerged as a robust approach to reveal condition-specific network modules, with successful applications in a few human disease studies. Hepatocellular carcinoma (HCC), which is often interrelated with the Hepatitis C virus, typically develops through multiple stages. A comprehensive investigation of HCC progression-specific differential co-expression modules may advance our understanding of HCC's pathophysiological mechanisms. |
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 % |
|---|---|---|
| United States | 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 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 23 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 26% |
| Student > Postgraduate | 5 | 22% |
| Student > Ph. D. Student | 5 | 22% |
| Student > Master | 3 | 13% |
| Lecturer | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 2 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 9 | 39% |
| Immunology and Microbiology | 5 | 22% |
| Biochemistry, Genetics and Molecular Biology | 2 | 9% |
| Medicine and Dentistry | 2 | 9% |
| Nursing and Health Professions | 1 | 4% |
| Other | 2 | 9% |
| Unknown | 2 | 9% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 08 November 2014.
All research outputs
#20,242,136
of 22,769,322 outputs
Outputs from BMC Systems Biology
#1,009
of 1,142 outputs
Outputs of similar age
#267,254
of 307,100 outputs
Outputs of similar age from BMC Systems Biology
#52
of 59 outputs
Altmetric has tracked 22,769,322 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 1st percentile – i.e., 1% 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 307,100 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 59 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.