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URDME: a modular framework for stochastic simulation of reaction-transport processes in complex geometries

Overview of attention for article published in BMC Systems Biology, June 2012
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Citations

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Title
URDME: a modular framework for stochastic simulation of reaction-transport processes in complex geometries
Published in
BMC Systems Biology, June 2012
DOI 10.1186/1752-0509-6-76
Pubmed ID
Authors

Brian Drawert, Stefan Engblom, Andreas Hellander

Abstract

Experiments in silico using stochastic reaction-diffusion models have emerged as an important tool in molecular systems biology. Designing computational software for such applications poses several challenges. Firstly, realistic lattice-based modeling for biological applications requires a consistent way of handling complex geometries, including curved inner- and outer boundaries. Secondly, spatiotemporal stochastic simulations are computationally expensive due to the fast time scales of individual reaction- and diffusion events when compared to the biological phenomena of actual interest. We therefore argue that simulation software needs to be both computationally efficient, employing sophisticated algorithms, yet in the same time flexible in order to meet present and future needs of increasingly complex biological modeling.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 4%
Switzerland 2 3%
Norway 1 1%
Japan 1 1%
Unknown 68 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 25 33%
Student > Ph. D. Student 20 27%
Student > Master 9 12%
Professor 5 7%
Professor > Associate Professor 2 3%
Other 4 5%
Unknown 10 13%
Readers by discipline Count As %
Computer Science 14 19%
Agricultural and Biological Sciences 14 19%
Mathematics 8 11%
Biochemistry, Genetics and Molecular Biology 7 9%
Engineering 5 7%
Other 17 23%
Unknown 10 13%

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 25 July 2012.
All research outputs
#15,055,021
of 18,796,975 outputs
Outputs from BMC Systems Biology
#816
of 1,127 outputs
Outputs of similar age
#102,693
of 137,792 outputs
Outputs of similar age from BMC Systems Biology
#22
of 29 outputs
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So far Altmetric has tracked 1,127 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
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We're also able to compare this research output to 29 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.