Compact Representation of Photosynthesis Dynamics by Rule-based Models (Full Version)

TL;DR

This paper introduces a rule-based modelling approach using a simplified Kappa language to create more compact and automatically reducible models of photosynthesis, addressing the combinatorial complexity of traditional methods.

Contribution

It demonstrates how rule-based models can efficiently represent and simplify photosynthesis dynamics, improving upon existing mass action kinetics models.

Findings

Rule-based models reduce model complexity

Automatic reduction of models is feasible

Demonstrated on multiple photosynthesis models

Abstract

Traditional mathematical models of photosynthesis are based on mass action kinetics of light reactions. This approach requires the modeller to enumerate all the possible state combinations of the modelled chemical species. This leads to combinatorial explosion in the number of reactions although the structure of the model could be expressed more compactly. We explore the use of rule-based modelling, in particular, a simplified variant of Kappa, to compactly capture and automatically reduce existing mathematical models of photosynthesis. Finally, the reduction procedure is implemented in BioNetGen language and demonstrated on several ODE models of photosynthesis processes. This is an extended version of the paper published in proceedings of 5th International Workshop on Static Analysis and Systems Biology (SASB) 2014.