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Mendeley readers
Attention Score in Context
Title |
Modeling biological gradient formation: combining partial differential equations and Petri nets
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Published in |
Natural Computing, October 2015
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DOI | 10.1007/s11047-015-9531-4 |
Pubmed ID | |
Authors |
Laura M. F. Bertens, Jetty Kleijn, Sander C. Hille, Monika Heiner, Maciej Koutny, Fons J. Verbeek |
Abstract |
Both Petri nets and differential equations are important modeling tools for biological processes. In this paper we demonstrate how these two modeling techniques can be combined to describe biological gradient formation. Parameters derived from partial differential equation describing the process of gradient formation are incorporated in an abstract Petri net model. The quantitative aspects of the resulting model are validated through a case study of gradient formation in the fruit fly. |
Mendeley readers
The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 13 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 2 | 15% |
Lecturer > Senior Lecturer | 1 | 8% |
Lecturer | 1 | 8% |
Student > Doctoral Student | 1 | 8% |
Student > Bachelor | 1 | 8% |
Other | 5 | 38% |
Unknown | 2 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 5 | 38% |
Engineering | 2 | 15% |
Agricultural and Biological Sciences | 1 | 8% |
Biochemistry, Genetics and Molecular Biology | 1 | 8% |
Chemistry | 1 | 8% |
Other | 1 | 8% |
Unknown | 2 | 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 June 2017.
All research outputs
#16,090,209
of 23,870,803 outputs
Outputs from Natural Computing
#88
of 147 outputs
Outputs of similar age
#169,873
of 286,961 outputs
Outputs of similar age from Natural Computing
#3
of 6 outputs
Altmetric has tracked 23,870,803 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 147 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 20th percentile – i.e., 20% 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 286,961 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.