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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Identification of dysfunctional modules and disease genes in congenital heart disease by a network-based approach
|
|---|---|
| Published in |
BMC Genomics, December 2011
|
| DOI | 10.1186/1471-2164-12-592 |
| Pubmed ID | |
| Authors |
Danning He, Zhi-Ping Liu, Luonan Chen |
| Abstract |
The incidence of congenital heart disease (CHD) is continuously increasing among infants born alive nowadays, making it one of the leading causes of infant morbidity worldwide. Various studies suggest that both genetic and environmental factors lead to CHD, and therefore identifying its candidate genes and disease-markers has been one of the central topics in CHD research. By using the high-throughput genomic data of CHD which are available recently, network-based methods provide powerful alternatives of systematic analysis of complex diseases and identification of dysfunctional modules and candidate disease genes. |
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 % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 6% |
| United Kingdom | 2 | 3% |
| France | 1 | 1% |
| Brazil | 1 | 1% |
| Mexico | 1 | 1% |
| Luxembourg | 1 | 1% |
| Unknown | 61 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 17 | 24% |
| Student > Ph. D. Student | 16 | 23% |
| Professor | 6 | 8% |
| Student > Bachelor | 6 | 8% |
| Student > Master | 6 | 8% |
| Other | 13 | 18% |
| Unknown | 7 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 20 | 28% |
| Biochemistry, Genetics and Molecular Biology | 14 | 20% |
| Medicine and Dentistry | 11 | 15% |
| Computer Science | 11 | 15% |
| Engineering | 3 | 4% |
| Other | 4 | 6% |
| Unknown | 8 | 11% |
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 11 June 2014.
All research outputs
#15,241,259
of 22,661,413 outputs
Outputs from BMC Genomics
#6,658
of 10,612 outputs
Outputs of similar age
#162,324
of 239,901 outputs
Outputs of similar age from BMC Genomics
#176
of 298 outputs
Altmetric has tracked 22,661,413 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,612 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 29th percentile – i.e., 29% 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 239,901 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 298 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.