Refining Boolean models with the partial most permissive scheme

TL;DR

This paper introduces MRBM, a method to refine Boolean models into multivalued models using a new updating scheme, improving the capture of specific dynamical properties in biological systems.

Contribution

The paper presents MRBM, a novel, efficient approach for multivaluing Boolean models to better represent fixed-point reachabilities in asynchronous dynamics.

Findings

MRBM accurately identifies components to multivalued in biological models.

The method is supported by mathematical proofs.

Demonstrated on stem cell differentiation models.

Abstract

Motivation: In systems biology, modelling strategies aim to decode how molecular components interact to generate dynamical behaviour. Boolean modelling is more and more used, but the description of the dynamics from two-levels components may be too limited to capture certain dynamical properties. %However, in Boolean models, the description of the dynamics may be too limited to capture certain dynamical properties. Multivalued logical models can overcome this limitation by allowing more than two levels for each component. However, multivaluing a Boolean model is challenging. Results: We present MRBM, a method for efficiently identifying the components of a Boolean model to be multivalued in order to capture specific fixed-point reachabilities in the asynchronous dynamics. To this goal, we defined a new updating scheme locating reachability properties in the most permissive dynamics. MRBM is supported by mathematical demonstrations and illustrated on a toy model and on two models of stem cell differentiation.