Modelling with ANIMO: between fuzzy logic and differential equations

BMC Systems Biology

Table 1 Comparison between ANIMO and some existing approaches to modelling biological systems

Tool	Formalism	Domain-specific interface	Visual modeling	Qualitative parameters	Tight coupling with topology	User-chosen granularity
GINsim [40]	Boolean Networks	Yes	Yes	Yes	Yes	Yes ^a
BooleSim [41]	Boolean Networks	Yes	Yes	No	No	No
CytoCopteR [35]	Fuzzy logic ^b	Yes	Yes	Yes	Yes	Yes ^c
ANIMO [10]	Timed Automata	Yes	Yes	Yes	Yes	Yes
Odefy [42]	Logic-based ODE	No	Yes ^d	Yes	No	No
COPASI [43]	ODE, stochastic models	No ^e	No	No	No	No
CellDesigner [44]	ODE	Yes	Yes	No	Yes	No
GNA [45]	PLDE	Yes	Yes	Yes	Yes	Yes ^a
Virtual Cell [46]	ODE, PDE, stochastic models	Yes	Yes	No	Yes	No
Bio-PEPA Workbench [47]	Bio-PEPA	No	No	No	No	Yes
COSBI LAB [48]	BlenX	Yes	Yes	No	Yes	No
Cell Illustrator [49]	Petri Nets	Yes	Yes	No	Yes	No

A “Yes” under a column indicates that the modelling tool (mostly) fulfils the parameter, “No” indicates very limited or no fulfilment
^aThe user can choose the number of levels for each reactant, allowing to define multi-level models based on Boolean reaction dynamics
^bBoolean logic and logic-based ODE models are also available
^cThe choice for the type of logic to be used determines also the granularity of the model
^dOnly if coupled with the yEd [50] graph editor
^eWhile visual network modeling is absent, the MultiState Model Builder (MSMB [51]) editor provides an interactive support during the phase of model definition

ISSN: 1752-0509