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Rosen's (M,R) system in process algebra.

Derek Gatherer1, Vashti Galpin

  • 1MRC-University of Glasgow Centre for Virus Research, 8 Church Street, Glasgow G11 5JR, UK. d.gatherer@lancaster.ac.uk.

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Summary
This summary is machine-generated.

This study models Robert Rosen's Metabolism-Replacement (M,R) system using Bio-PEPA, finding it exhibits life-like properties and potentially sidesteps computability issues in systems biology.

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Area of Science:

  • Systems Biology
  • Theoretical Biology
  • Computational Biology

Background:

  • Robert Rosen's Metabolism-Replacement (M,R) system is a compact network with a single source and three sequential reactions.
  • The (M,R) system is claimed to be non-reducible and algorithmically non-computable.
  • Presence of (M,R)-like structures in biological networks implies potential non-computability, challenging in silico modeling in systems biology.

Purpose of the Study:

  • To instantiate Robert Rosen's (M,R) system using the process algebra Bio-PEPA.
  • To explore the computability and life-like properties of the (M,R) system within a computational framework.
  • To address Rosen's objections to computational systems biology.

Main Methods:

  • Modeling the (M,R) system using Bio-PEPA, a process algebra.
  • Analyzing the model's behavior under various starting conditions and parameter values.
  • Investigating the implications of the Bio-PEPA model for algorithmic computability.

Main Results:

  • The Bio-PEPA instantiation of the (M,R) system can achieve stable states under specific conditions.
  • The model allows for a discussion on sidestepping formal objections to computational systems biology.
  • Algorithmic computability for the core (M,R) system remains formally elusive.

Conclusions:

  • The behavior of the (M,R) system modeled in Bio-PEPA demonstrates life-like properties.
  • This computational approach offers a way to engage with complex biological systems that may possess non-computable characteristics.
  • The study highlights the potential of process algebra in modeling fundamental biological concepts.