Journal of Computer and System Sciences
Handbook of Formal Languages
Artificial chemistries—a review
Artificial Life
Membrane Computing: An Introduction
Membrane Computing: An Introduction
Investigating Local Evolutions in Dynamical Probabilistic P Systems
SYNASC '05 Proceedings of the Seventh International Symposium on Symbolic and Numeric Algorithms for Scientific Computing
Discrete solutions to differential equations by metabolic P systems
Theoretical Computer Science
Towards evolutionary network reconstruction tools for systems biology
EvoBIO'07 Proceedings of the 5th European conference on Evolutionary computation, machine learning and data mining in bioinformatics
WMC'07 Proceedings of the 8th international conference on Membrane computing
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Complex reaction systems in molecular biology are often composed of partially independent subsystems associated with the activity of external or internal triggers. Occurring as random events or dedicated physical signals, triggers effect transitions from one subsystem to another which might result in substantial changes of detectable behavior. From a modeling point of view, those subsystems typically differ in their reaction rules or principle of operation. We propose a formulation of trigger-based switching between models from a class of P systems with progression in time employing discretized mass-action kinetics. Two examples inspired by biological phenomena illustrate the consecutive interplay of P systems towards structural plasticity in reaction rules: evolutionary construction of reaction networks and artificial chemistries with self-reproducible subunits.