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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Inference of gene pathways using mixture Bayesian networks
|
|---|---|
| Published in |
BMC Systems Biology, May 2009
|
| DOI | 10.1186/1752-0509-3-54 |
| Pubmed ID | |
| Authors |
Younhee Ko, ChengXiang Zhai, Sandra Rodriguez-Zas |
| Abstract |
Inference of gene networks typically relies on measurements across a wide range of conditions or treatments. Although one network structure is predicted, the relationship between genes could vary across conditions. A comprehensive approach to infer general and condition-dependent gene networks was evaluated. This approach integrated Bayesian network and Gaussian mixture models to describe continuous microarray gene expression measurements, and three gene networks were predicted. |
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 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 10% |
| Germany | 3 | 5% |
| Hong Kong | 1 | 2% |
| Netherlands | 1 | 2% |
| Brazil | 1 | 2% |
| Australia | 1 | 2% |
| Unknown | 50 | 79% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 25% |
| Researcher | 15 | 24% |
| Professor | 8 | 13% |
| Professor > Associate Professor | 7 | 11% |
| Student > Master | 5 | 8% |
| Other | 7 | 11% |
| Unknown | 5 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 24 | 38% |
| Computer Science | 14 | 22% |
| Biochemistry, Genetics and Molecular Biology | 7 | 11% |
| Mathematics | 4 | 6% |
| Engineering | 3 | 5% |
| Other | 5 | 8% |
| Unknown | 6 | 10% |
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 25 May 2012.
All research outputs
#20,157,329
of 22,665,794 outputs
Outputs from BMC Systems Biology
#1,010
of 1,142 outputs
Outputs of similar age
#93,050
of 96,922 outputs
Outputs of similar age from BMC Systems Biology
#6
of 6 outputs
Altmetric has tracked 22,665,794 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 96,922 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 6 others from the same source and published within six weeks on either side of this one.