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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Dynamic probabilistic threshold networks to infer signaling pathways from time-course perturbation data
|
|---|---|
| Published in |
BMC Bioinformatics, July 2014
|
| DOI | 10.1186/1471-2105-15-250 |
| Pubmed ID | |
| Authors |
Narsis A Kiani, Lars Kaderali |
| Abstract |
Network inference deals with the reconstruction of molecular networks from experimental data. Given N molecular species, the challenge is to find the underlying network. Due to data limitations, this typically is an ill-posed problem, and requires the integration of prior biological knowledge or strong regularization. We here focus on the situation when time-resolved measurements of a system's response after systematic perturbations are available. |
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 % |
|---|---|---|
| Norway | 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 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 4% |
| France | 1 | 2% |
| Brazil | 1 | 2% |
| Denmark | 1 | 2% |
| United States | 1 | 2% |
| Luxembourg | 1 | 2% |
| Unknown | 40 | 85% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 30% |
| Researcher | 13 | 28% |
| Student > Bachelor | 4 | 9% |
| Student > Master | 3 | 6% |
| Professor | 3 | 6% |
| Other | 3 | 6% |
| Unknown | 7 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 12 | 26% |
| Biochemistry, Genetics and Molecular Biology | 9 | 19% |
| Computer Science | 6 | 13% |
| Medicine and Dentistry | 4 | 9% |
| Mathematics | 2 | 4% |
| Other | 6 | 13% |
| Unknown | 8 | 17% |
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 July 2014.
All research outputs
#19,017,658
of 23,577,761 outputs
Outputs from BMC Bioinformatics
#6,465
of 7,418 outputs
Outputs of similar age
#165,285
of 230,235 outputs
Outputs of similar age from BMC Bioinformatics
#104
of 129 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,418 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 5th percentile – i.e., 5% 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 230,235 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 129 others from the same source and published within six weeks on either side of this one. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.