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Mendeley readers
Attention Score in Context
| Chapter title |
Logical Modelling of Gene Regulatory Networks with GINsim.
|
|---|---|
| Chapter number | 23 |
| Book title |
Bacterial Molecular Networks
|
| Published in |
Methods in molecular biology, December 2011
|
| DOI | 10.1007/978-1-61779-361-5_23 |
| Pubmed ID | |
| Book ISBNs |
978-1-61779-360-8, 978-1-61779-361-5
|
| Authors |
Chaouiya C, Naldi A, Thieffry D, Claudine Chaouiya, Aurélien Naldi, Denis Thieffry, Chaouiya, Claudine, Naldi, Aurélien, Thieffry, Denis |
| Abstract |
Discrete mathematical formalisms are well adapted to model large biological networks, for which detailed kinetic data are scarce. This chapter introduces the reader to a well-established qualitative (logical) framework for the modelling of regulatory networks. Relying on GINsim, a software implementing this logical formalism, we guide the reader step by step towards the definition and the analysis of a simple model of the lysis-lysogeny decision in the bacteriophage λ. |
Mendeley readers
The data shown below were compiled from readership statistics for 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 3 | 3% |
| Italy | 1 | 1% |
| Portugal | 1 | 1% |
| Unknown | 81 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 22 | 26% |
| Researcher | 22 | 26% |
| Student > Master | 16 | 19% |
| Student > Bachelor | 4 | 5% |
| Professor | 4 | 5% |
| Other | 11 | 13% |
| Unknown | 7 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 25 | 29% |
| Biochemistry, Genetics and Molecular Biology | 20 | 23% |
| Computer Science | 11 | 13% |
| Engineering | 5 | 6% |
| Immunology and Microbiology | 3 | 3% |
| Other | 9 | 10% |
| Unknown | 13 | 15% |
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 15 December 2014.
All research outputs
#20,246,428
of 22,774,233 outputs
Outputs from Methods in molecular biology
#9,866
of 13,091 outputs
Outputs of similar age
#219,304
of 241,158 outputs
Outputs of similar age from Methods in molecular biology
#410
of 463 outputs
Altmetric has tracked 22,774,233 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 13,091 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 1st percentile – i.e., 1% 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 241,158 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 463 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.