Modelling with ANIMO: between fuzzy logic and differential equations.BACKGROUND
 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.


 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.  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.
ANIMO
Modelling with ANIMO: between fuzzy logic and differential equations.BACKGROUND
 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.


 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.  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.
ANIMO
Modelling with ANIMO: between fuzzy logic and differential equations.BACKGROUND
 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.


 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.  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.
ANIMO