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ZENODO
Dataset . 2017
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2017
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2017
License: CC BY
Data sources: Datacite
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https://doi.org/10.5281/zenodo...
Dataset . 2017
License: CC BY
Data sources: Sygma
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Dataset Supporting The Paper: Symbolic Versus Numerical Computation And Visualization Of Parameter Regions For Multistationarity Of Biological Networks

Authors: England, Matthew; Errami, Hassan; Grigoriev, Dima; Radulescu, Ovidiu; Sturm, Thomas; Weber, Andreas;

Dataset Supporting The Paper: Symbolic Versus Numerical Computation And Visualization Of Parameter Regions For Multistationarity Of Biological Networks

Abstract

Dataset supporting the paper: Matthew England, Hassan Errami, Dima Grigoriev, Ovidiu Radulescu, Thomas Sturm, and Andreas Weber. Symbolic Versus Numerical Computation and Visualization of Parameter Regions for Multistationarity of Biological Networks. In Proceedings of CASC ’17, Beijing, China, September 18-22 2017, 15 pages. Springer, 2017. The files whose name starts with "SamplePoints" are text files containing the data that produced the plots in the paper. The files whose name starts with "Sys" show the Maple computations used to produce the data. The mw files are to be run with the Maple Computer Algebra System (https://www.maplesoft.com/products/maple/). Pdf printouts of these have also been included for those who do not have access to Maple.

{"references": ["Matthew England, Hassan Errami, Dima Grigoriev, Ovidiu Radulescu,\u00a0Thomas Sturm, and Andreas Weber. Symbolic Versus Numerical Computation and Visualization of Parameter Regions for Multistationarity of Biological Networks. \u00a0In Proceedings of CASC\u00a0'17, Beijing, China, September 18-22 2017, 15\u00a0pages. Springer, 2017."]}

Keywords

Biological Networks, Symbolic Computation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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