Modelling with ANIMO: between fuzzy logic and differential equations

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  • 6 Citations

Abstract

Background Computational support is essential in order to reason on the dynamics of biological systems. We have developed the software tool ANIMO (Analysis of Networks with Interactive MOdeling) to provide such computational support and allow insight into the complex networks of signaling events occurring in living cells. ANIMO makes use of timed automata as an underlying model, thereby enabling analysis techniques from computer science like model checking. Biology experts are able to use ANIMO via a user interface specifically tailored for biological applications. In this paper we compare the use of ANIMO with some established formalisms on two case studies. Results ANIMO is a powerful and user-friendly tool that can compete with existing continuous and discrete paradigms. We show this by presenting ANIMO models for two case studies: Drosophila melanogaster circadian clock, and signal transduction events downstream of TNF α and EGF in HT-29 human colon carcinoma cells. The models were originally developed with ODEs and fuzzy logic, respectively. Conclusions Two biological case studies that have been modeled with respectively ODE and fuzzy logic models can be conveniently modeled using ANIMO. The ANIMO models require less parameters than ODEs and are more precise than fuzzy logic. For this reason we position the modelling paradigm of ANIMO between ODEs and fuzzy logic.
LanguageUndefined
Pages56
Number of pages15
JournalBMC systems biology
Volume10
DOIs
StatePublished - 27 Jul 2016

Keywords

  • EWI-27173
  • Timed Automata
  • Modelling
  • IR-101364
  • Signalling pathway
  • METIS-318502
  • Dynamic behaviour

Cite this

@article{5184377aff31429f840e8a0f6ff4e67b,
title = "Modelling with ANIMO: between fuzzy logic and differential equations",
abstract = "Background Computational support is essential in order to reason on the dynamics of biological systems. We have developed the software tool ANIMO (Analysis of Networks with Interactive MOdeling) to provide such computational support and allow insight into the complex networks of signaling events occurring in living cells. ANIMO makes use of timed automata as an underlying model, thereby enabling analysis techniques from computer science like model checking. Biology experts are able to use ANIMO via a user interface specifically tailored for biological applications. In this paper we compare the use of ANIMO with some established formalisms on two case studies. Results ANIMO is a powerful and user-friendly tool that can compete with existing continuous and discrete paradigms. We show this by presenting ANIMO models for two case studies: Drosophila melanogaster circadian clock, and signal transduction events downstream of TNF α and EGF in HT-29 human colon carcinoma cells. The models were originally developed with ODEs and fuzzy logic, respectively. Conclusions Two biological case studies that have been modeled with respectively ODE and fuzzy logic models can be conveniently modeled using ANIMO. The ANIMO models require less parameters than ODEs and are more precise than fuzzy logic. For this reason we position the modelling paradigm of ANIMO between ODEs and fuzzy logic.",
keywords = "EWI-27173, Timed Automata, Modelling, IR-101364, Signalling pathway, METIS-318502, Dynamic behaviour",
author = "Stefano Schivo and Jetse Scholma and {van der Vet}, P.E. and Karperien, {Hermanus Bernardus Johannes} and Post, {Janine Nicole} and {van de Pol}, {Jan Cornelis} and Romanus Langerak",
note = "Open access",
year = "2016",
month = "7",
day = "27",
doi = "10.1186/s12918-016-0286-z",
language = "Undefined",
volume = "10",
pages = "56",
journal = "BMC systems biology",
issn = "1752-0509",
publisher = "BioMed Central",

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T1 - Modelling with ANIMO: between fuzzy logic and differential equations

AU - Schivo,Stefano

AU - Scholma,Jetse

AU - van der Vet,P.E.

AU - Karperien,Hermanus Bernardus Johannes

AU - Post,Janine Nicole

AU - van de Pol,Jan Cornelis

AU - Langerak,Romanus

N1 - Open access

PY - 2016/7/27

Y1 - 2016/7/27

N2 - Background Computational support is essential in order to reason on the dynamics of biological systems. We have developed the software tool ANIMO (Analysis of Networks with Interactive MOdeling) to provide such computational support and allow insight into the complex networks of signaling events occurring in living cells. ANIMO makes use of timed automata as an underlying model, thereby enabling analysis techniques from computer science like model checking. Biology experts are able to use ANIMO via a user interface specifically tailored for biological applications. In this paper we compare the use of ANIMO with some established formalisms on two case studies. Results ANIMO is a powerful and user-friendly tool that can compete with existing continuous and discrete paradigms. We show this by presenting ANIMO models for two case studies: Drosophila melanogaster circadian clock, and signal transduction events downstream of TNF α and EGF in HT-29 human colon carcinoma cells. The models were originally developed with ODEs and fuzzy logic, respectively. Conclusions Two biological case studies that have been modeled with respectively ODE and fuzzy logic models can be conveniently modeled using ANIMO. The ANIMO models require less parameters than ODEs and are more precise than fuzzy logic. For this reason we position the modelling paradigm of ANIMO between ODEs and fuzzy logic.

AB - Background Computational support is essential in order to reason on the dynamics of biological systems. We have developed the software tool ANIMO (Analysis of Networks with Interactive MOdeling) to provide such computational support and allow insight into the complex networks of signaling events occurring in living cells. ANIMO makes use of timed automata as an underlying model, thereby enabling analysis techniques from computer science like model checking. Biology experts are able to use ANIMO via a user interface specifically tailored for biological applications. In this paper we compare the use of ANIMO with some established formalisms on two case studies. Results ANIMO is a powerful and user-friendly tool that can compete with existing continuous and discrete paradigms. We show this by presenting ANIMO models for two case studies: Drosophila melanogaster circadian clock, and signal transduction events downstream of TNF α and EGF in HT-29 human colon carcinoma cells. The models were originally developed with ODEs and fuzzy logic, respectively. Conclusions Two biological case studies that have been modeled with respectively ODE and fuzzy logic models can be conveniently modeled using ANIMO. The ANIMO models require less parameters than ODEs and are more precise than fuzzy logic. For this reason we position the modelling paradigm of ANIMO between ODEs and fuzzy logic.

KW - EWI-27173

KW - Timed Automata

KW - Modelling

KW - IR-101364

KW - Signalling pathway

KW - METIS-318502

KW - Dynamic behaviour

U2 - 10.1186/s12918-016-0286-z

DO - 10.1186/s12918-016-0286-z

M3 - Article

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SP - 56

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