Reaction Systems (RSs) were introduced in the field of natural computing as a qualitative model inspired by biological systems. In a RS, each reaction comprises a set of reactants that generate products unless inhibited by reaction inhibitors. We propose a method for analyzing the attractors of a RS model (the states to which the system converges) and for identifying the entities responsible for their attainment. Our approach builds on (i) the construction of a Labeled Transition System (LTS) based on a formal SOS semantics of RSs, and (ii) the application of a slicing method to the trajectories within the LTS. Our model analysis provides new insights with respect to previous studies. We illustrate our methodology on a case study that demonstrates its capability to identify stimulus combinations that lead to specific phenotypes, but also to elucidate the involvement of proteins within T cells in each scenario. These findings allow for a better understanding of the phenomenon and for the identification of potential drug targets for diseases.

Attractor and Slicing Analysis of a T Cell Differentiation Model Based on Reaction Systems

Bruni, Roberto;Gori, Roberta;Milazzo, Paolo
2025-01-01

Abstract

Reaction Systems (RSs) were introduced in the field of natural computing as a qualitative model inspired by biological systems. In a RS, each reaction comprises a set of reactants that generate products unless inhibited by reaction inhibitors. We propose a method for analyzing the attractors of a RS model (the states to which the system converges) and for identifying the entities responsible for their attainment. Our approach builds on (i) the construction of a Labeled Transition System (LTS) based on a formal SOS semantics of RSs, and (ii) the application of a slicing method to the trajectories within the LTS. Our model analysis provides new insights with respect to previous studies. We illustrate our methodology on a case study that demonstrates its capability to identify stimulus combinations that lead to specific phenotypes, but also to elucidate the involvement of proteins within T cells in each scenario. These findings allow for a better understanding of the phenomenon and for the identification of potential drug targets for diseases.
2025
9783031872167
9783031872174
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1315248
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