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Autocatalytic recombination systems: A reaction network perspective.

Gheorghe Craciun1, Abhishek Deshpande2, Badal Joshi3

  • 1Department of Mathematics and Department of Biomolecular Chemistry, University of Wisconsin-Madison, United States of America.

Mathematical Biosciences
|February 8, 2022
PubMed
Summary

This study analyzes bimolecular autocatalytic systems, relevant to origin of life research. We demonstrate their dynamics can be modeled using polynomial systems, proving the persistence of autocatalytic recombination systems.

Keywords:
Autocatalytic recombination networksOrigin of lifePermanencePersistence

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Area of Science:

  • Chemical kinetics
  • Systems chemistry
  • Origin of life research

Background:

  • Hypercycles are frequently used in origin of life models.
  • Bimolecular autocatalytic systems are related models with complex dynamics.

Purpose of the Study:

  • Investigate the dynamics of bimolecular autocatalytic systems.
  • Analyze the relative population dynamics within these networks.
  • Prove the persistence and permanence of specific autocatalytic systems.

Main Methods:

  • Modeling dynamics using autonomous polynomial dynamical systems.
  • Applying reaction network theory.
  • Analyzing population dynamics and system stability.

Main Results:

  • Demonstrated that relative population dynamics can be analyzed with polynomial systems.
  • Proved persistence and permanence for families of autocatalytic recombination systems.
  • Provided a mathematical framework for understanding these systems.

Conclusions:

  • Bimolecular autocatalytic systems exhibit dynamics amenable to analysis via polynomial systems.
  • Reaction network theory confirms the stability and persistence of autocatalytic recombination systems.
  • This work contributes to understanding the fundamental principles governing self-organizing chemical systems relevant to abiogenesis.