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Mendeley readers
Attention Score in Context
Title |
Oscillatory Regulation of Hes1: Discrete Stochastic Delay Modelling and Simulation
|
---|---|
Published in |
PLoS Computational Biology, September 2006
|
DOI | 10.1371/journal.pcbi.0020117 |
Pubmed ID | |
Authors |
Manuel Barrio, Kevin Burrage, André Leier, Tianhai Tian |
Abstract |
Discrete stochastic simulations are a powerful tool for understanding the dynamics of chemical kinetics when there are small-to-moderate numbers of certain molecular species. In this paper we introduce delays into the stochastic simulation algorithm, thus mimicking delays associated with transcription and translation. We then show that this process may well explain more faithfully than continuous deterministic models the observed sustained oscillations in expression levels of hes1 mRNA and Hes1 protein. |
Mendeley readers
The data shown below were compiled from readership statistics for 155 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 3 | 2% |
United States | 2 | 1% |
Mexico | 2 | 1% |
Chile | 1 | <1% |
France | 1 | <1% |
Switzerland | 1 | <1% |
Portugal | 1 | <1% |
Japan | 1 | <1% |
Argentina | 1 | <1% |
Other | 0 | 0% |
Unknown | 142 | 92% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 47 | 30% |
Researcher | 40 | 26% |
Student > Master | 12 | 8% |
Professor | 9 | 6% |
Student > Bachelor | 6 | 4% |
Other | 24 | 15% |
Unknown | 17 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 42 | 27% |
Biochemistry, Genetics and Molecular Biology | 23 | 15% |
Mathematics | 18 | 12% |
Computer Science | 15 | 10% |
Physics and Astronomy | 12 | 8% |
Other | 23 | 15% |
Unknown | 22 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 04 January 2024.
All research outputs
#8,534,528
of 25,373,627 outputs
Outputs from PLoS Computational Biology
#5,636
of 8,960 outputs
Outputs of similar age
#30,531
of 88,961 outputs
Outputs of similar age from PLoS Computational Biology
#17
of 33 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,960 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 33rd percentile – i.e., 33% 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 88,961 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.