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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Inferring slowly-changing dynamic gene-regulatory networks
|
|---|---|
| Published in |
BMC Bioinformatics, April 2015
|
| DOI | 10.1186/1471-2105-16-s6-s5 |
| Pubmed ID | |
| Authors |
Ernst C Wit, Antonino Abbruzzo |
| Abstract |
Dynamic gene-regulatory networks are complex since the interaction patterns between their components mean that it is impossible to study parts of the network in separation. This holistic character of gene-regulatory networks poses a real challenge to any type of modelling. Graphical models are a class of models that connect the network with a conditional independence relationships between random variables. By interpreting these random variables as gene activities and the conditional independence relationships as functional non-relatedness, graphical models have been used to describe gene-regulatory networks. Whereas the literature has been focused on static networks, most time-course experiments are designed in order to tease out temporal changes in the underlying network. It is typically reasonable to assume that changes in genomic networks are few, because biological systems tend to be stable. |
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 | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 6% |
| Spain | 1 | 3% |
| Unknown | 28 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 39% |
| Researcher | 5 | 16% |
| Student > Doctoral Student | 3 | 10% |
| Student > Master | 3 | 10% |
| Professor | 1 | 3% |
| Other | 3 | 10% |
| Unknown | 4 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 9 | 29% |
| Mathematics | 5 | 16% |
| Biochemistry, Genetics and Molecular Biology | 4 | 13% |
| Computer Science | 3 | 10% |
| Economics, Econometrics and Finance | 1 | 3% |
| Other | 4 | 13% |
| Unknown | 5 | 16% |
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 22 September 2015.
All research outputs
#17,758,492
of 22,805,349 outputs
Outputs from BMC Bioinformatics
#5,930
of 7,281 outputs
Outputs of similar age
#180,678
of 264,844 outputs
Outputs of similar age from BMC Bioinformatics
#124
of 144 outputs
Altmetric has tracked 22,805,349 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,281 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 13th percentile – i.e., 13% 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 264,844 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 144 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.