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Mendeley readers
Attention Score in Context
| Title |
Noise Decomposition Principle in a Coherent Feed-Forward Transcriptional Regulatory Loop
|
|---|---|
| Published in |
Frontiers in Physiology, November 2016
|
| DOI | 10.3389/fphys.2016.00600 |
| Pubmed ID | |
| Authors |
Rong Gui, Quan Liu, Yuangen Yao, Haiyou Deng, Chengzhang Ma, Ya Jia, Ming Yi |
| Abstract |
Coherent feed-forward loops exist extensively in realistic biological regulatory systems, and are common signaling motifs. Here, we study the characteristics and the propagation mechanism of the output noise in a coherent feed-forward transcriptional regulatory loop that can be divided into a main road and branch. Using the linear noise approximation, we derive analytical formulae for the total noise of the full loop, the noise of the branch, and the noise of the main road, which are verified by the Gillespie algorithm. Importantly, we find that (i) compared with the branch motif or the main road motif, the full motif can effectively attenuate the output noise level; (ii) there is a transition point of system state such that the noise of the main road is dominated when the underlying system is below this point, whereas the noise of the branch is dominated when the system is beyond the point. The entire analysis reveals the mechanism of how the noise is generated and propagated in a simple yet representative signaling module. |
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 % |
|---|---|---|
| Switzerland | 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 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 41% |
| Researcher | 2 | 9% |
| Student > Master | 2 | 9% |
| Student > Doctoral Student | 1 | 5% |
| Other | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 7 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 8 | 36% |
| Computer Science | 2 | 9% |
| Agricultural and Biological Sciences | 1 | 5% |
| Mathematics | 1 | 5% |
| Chemistry | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 8 | 36% |
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 02 December 2016.
All research outputs
#20,355,479
of 22,903,988 outputs
Outputs from Frontiers in Physiology
#9,425
of 13,694 outputs
Outputs of similar age
#349,990
of 415,970 outputs
Outputs of similar age from Frontiers in Physiology
#152
of 220 outputs
Altmetric has tracked 22,903,988 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 13,694 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 220 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.