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X Demographics
Mendeley readers
Attention Score in Context
Chapter title |
Evolution In Silico: From Network Structure to Bifurcation Theory
|
---|---|
Chapter number | 8 |
Book title |
Evolutionary Systems Biology
|
Published in |
Advances in experimental medicine and biology, June 2012
|
DOI | 10.1007/978-1-4614-3567-9_8 |
Pubmed ID | |
Book ISBNs |
978-1-4614-3566-2, 978-1-4614-3567-9
|
Authors |
Paul François |
Editors |
Orkun S. Soyer |
Abstract |
I describe an evolutionary procedure in silico that creates small gene networks performing basic tasks. I use it to evolve a wide range of models for very different biological functions: multistability, adaptive networks and entire developmental programmes like somitogenesis and Hox gene pattern. In silico evolution finds both known and original network designs, and can be used to make predictions on biological behaviours. This computation illustrates how complex traits can evolve in an incremental way, and suggests that dynamical systems theory could be used to get new insights towards a predictive evolutionary theory. |
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 % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Slovenia | 1 | 4% |
Unknown | 22 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 5 | 22% |
Student > Ph. D. Student | 4 | 17% |
Student > Bachelor | 3 | 13% |
Professor | 3 | 13% |
Student > Doctoral Student | 2 | 9% |
Other | 3 | 13% |
Unknown | 3 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 6 | 26% |
Biochemistry, Genetics and Molecular Biology | 3 | 13% |
Physics and Astronomy | 3 | 13% |
Computer Science | 2 | 9% |
Immunology and Microbiology | 2 | 9% |
Other | 4 | 17% |
Unknown | 3 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 09 April 2015.
All research outputs
#3,990,021
of 22,673,450 outputs
Outputs from Advances in experimental medicine and biology
#655
of 4,904 outputs
Outputs of similar age
#27,786
of 166,776 outputs
Outputs of similar age from Advances in experimental medicine and biology
#3
of 25 outputs
Altmetric has tracked 22,673,450 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,904 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one has done well, scoring higher than 86% of its peers.
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 166,776 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.