Abstract
We discuss some motivational challenges arising from the need to model and analyse complex biological systems at multiple scales (spatial and temporal), and present a biomodel engineering framework to address some of these issues within the context of multiscale Systems Biology. Our methodology is based on a structured family of Petri net classes which enables the investigation of a given system using various modelling abstractions: qualitative, stochastic, continuous and hybrid, optionally in a spatial context. We illustrate our approach with case studies demonstrating hierarchical flattening, treatment of space, and hierarchical organisation of space.
Highlights
MotivationBiological systems can be represented as networks which themselves typically contain regular (network) structures, and/or repeated occurrences of network patterns
The model has been encoded in Hierarchically Coloured Petri nets which we have considered both con(tci)nuously and sto(cd)hastically, where the core of the model comprises a description of the Planar cell polarity (PCP) signalling network within one virtual compartment, and colours employed to describe the relationship between adjacent compartments in neighbouring cells
In this paper we have presented a discussion of some challenges arising from the need to model and analyse complex biological systems at multiple scales, both spatial and temporal
Summary
Biological systems can be represented as networks which themselves typically contain regular (network) structures, and/or repeated occurrences of network patterns This organisation occurs in a hierarchical manner, reflecting the physical and spatial organisation of the organism, from the intracellular to the intercellular level and beyond (tissues, organs, etc.). Models should explicitly reflect the hierarchical organisation in complex biological systems
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