A computational method to preclude multistationarity in networks of interacting species

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Standard

A computational method to preclude multistationarity in networks of interacting species. / Feliu, Elisenda; Wiuf, Carsten.

I: Bioinformatics, Bind 29, Nr. 18, 2013, s. 2327-2334.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Feliu, E & Wiuf, C 2013, 'A computational method to preclude multistationarity in networks of interacting species', Bioinformatics, bind 29, nr. 18, s. 2327-2334. https://doi.org/10.1093/bioinformatics/btt400

APA

Feliu, E., & Wiuf, C. (2013). A computational method to preclude multistationarity in networks of interacting species. Bioinformatics, 29(18), 2327-2334. https://doi.org/10.1093/bioinformatics/btt400

Vancouver

Feliu E, Wiuf C. A computational method to preclude multistationarity in networks of interacting species. Bioinformatics. 2013;29(18):2327-2334. https://doi.org/10.1093/bioinformatics/btt400

Author

Feliu, Elisenda ; Wiuf, Carsten. / A computational method to preclude multistationarity in networks of interacting species. I: Bioinformatics. 2013 ; Bind 29, Nr. 18. s. 2327-2334.

Bibtex

@article{ccd588f859cb4d4f87a40b47a9072400,
title = "A computational method to preclude multistationarity in networks of interacting species",
abstract = "Modeling and analysis of complex systems are important aspects of understanding systemic behavior. In the lack of detailed knowledge about a system, we often choose modeling equations out of convenience and search the (high-dimensional) parameter space randomly to learn about model properties. Qualitative modeling sidesteps the issue of choosing specific modeling equations and frees the inference from specific properties of the equations. We consider classes of ODE models arising from interactions of species/entities, such as (bio)chemical reaction networks or ecosystems. A class is defined by imposing mild assumptions on the interaction rates. In this framework, we investigate whether there can be multiple positive steady states in some ODE models in a given class.",
author = "Elisenda Feliu and Carsten Wiuf",
year = "2013",
doi = "10.1093/bioinformatics/btt400",
language = "English",
volume = "29",
pages = "2327--2334",
journal = "Computer Applications in the Biosciences",
issn = "1471-2105",
publisher = "Oxford University Press",
number = "18",

}

RIS

TY - JOUR

T1 - A computational method to preclude multistationarity in networks of interacting species

AU - Feliu, Elisenda

AU - Wiuf, Carsten

PY - 2013

Y1 - 2013

N2 - Modeling and analysis of complex systems are important aspects of understanding systemic behavior. In the lack of detailed knowledge about a system, we often choose modeling equations out of convenience and search the (high-dimensional) parameter space randomly to learn about model properties. Qualitative modeling sidesteps the issue of choosing specific modeling equations and frees the inference from specific properties of the equations. We consider classes of ODE models arising from interactions of species/entities, such as (bio)chemical reaction networks or ecosystems. A class is defined by imposing mild assumptions on the interaction rates. In this framework, we investigate whether there can be multiple positive steady states in some ODE models in a given class.

AB - Modeling and analysis of complex systems are important aspects of understanding systemic behavior. In the lack of detailed knowledge about a system, we often choose modeling equations out of convenience and search the (high-dimensional) parameter space randomly to learn about model properties. Qualitative modeling sidesteps the issue of choosing specific modeling equations and frees the inference from specific properties of the equations. We consider classes of ODE models arising from interactions of species/entities, such as (bio)chemical reaction networks or ecosystems. A class is defined by imposing mild assumptions on the interaction rates. In this framework, we investigate whether there can be multiple positive steady states in some ODE models in a given class.

U2 - 10.1093/bioinformatics/btt400

DO - 10.1093/bioinformatics/btt400

M3 - Journal article

C2 - 23842805

VL - 29

SP - 2327

EP - 2334

JO - Computer Applications in the Biosciences

JF - Computer Applications in the Biosciences

SN - 1471-2105

IS - 18

ER -

ID: 47449828