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  Symbolic Versus Numerical Computation and Visualization of Parameter Regions for Multistationarity of Biological Networks

England, M., Errami, H., Grigoriev, D., Radulescu, O., Sturm, T., & Weber, A. (2017). Symbolic Versus Numerical Computation and Visualization of Parameter Regions for Multistationarity of Biological Networks. Retrieved from http://arxiv.org/abs/1706.08794.

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arXiv:1706.08794.pdf (Preprint), 2MB
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arXiv:1706.08794.pdf
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File downloaded from arXiv at 2017-07-11 11:01 Accepted into Proc. CASC 2017
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 Creators:
England, Matthew1, Author
Errami, Hassan1, Author
Grigoriev, Dima1, Author
Radulescu, Ovidiu1, Author
Sturm, Thomas2, Author           
Weber, Andreas1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Automation of Logic, MPI for Informatics, Max Planck Society, ou_1116545              

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Free keywords: Computer Science, Symbolic Computation, cs.SC
 Abstract: We investigate models of the mitogenactivated protein kinases (MAPK) network, with the aim of determining where in parameter space there exist multiple positive steady states. We build on recent progress which combines various symbolic computation methods for mixed systems of equalities and inequalities. We demonstrate that those techniques benefit tremendously from a newly implemented graph theoretical symbolic preprocessing method. We compare computation times and quality of results of numerical continuation methods with our symbolic approach before and after the application of our preprocessing.

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Language(s): eng - English
 Dates: 2017-06-272017
 Publication Status: Published online
 Pages: 15 p.
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: arXiv: 1706.08794
URI: http://arxiv.org/abs/1706.08794
BibTex Citekey: DBLP:journals/corr/EnglandEGR0017
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