Rule-based Modelling and Tunable Resolution

TL;DR

This paper presents an extension of rule-based modelling that allows for creating a structured space of model variants, enabling incremental development from simple to detailed cellular signalling models.

Contribution

It introduces a method for systematically increasing model resolution in rule-based models, facilitating stepwise refinement of cellular signalling simulations.

Findings

Structured model variant space enables incremental complexity

Supports gradual transition from simple to detailed models

Enhances flexibility in cellular signalling modelling

Abstract

We investigate the use of an extension of rule-based modelling for cellular signalling to create a structured space of model variants. This enables the incremental development of rule sets that start from simple mechanisms and which, by a gradual increase in agent and rule resolution, evolve into more detailed descriptions.