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Toward Engineering Biosystems With Emergent Collective Functions.

Thomas E Gorochowski1, Sabine Hauert2, Jan-Ulrich Kreft3

  • 1School of Biological Sciences, University of Bristol, Bristol, United Kingdom.

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Summary
This summary is machine-generated.

This study introduces multi-agent modeling as a synthetic biology design framework to engineer complex biological functions. It enables understanding and designing emergent collective behaviors across multiple scales.

Keywords:
bioengineeringcollectivesconsortiaemergencemulti-agent modelingmulti-scalesynthetic biologysystems biology

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Area of Science:

  • Synthetic Biology
  • Systems Biology
  • Computational Biology

Background:

  • Complex biological functions emerge from interacting populations of molecules or cells.
  • Engineering these emergent collective phenomena is challenging due to multi-level feedback across scales.
  • Bioengineers are interested in collective phenomena for their robustness and scalability.

Purpose of the Study:

  • To present multi-agent modeling as a design framework for synthetic biology.
  • To demonstrate how multi-agent modeling can address challenges in engineering emergent collective functions.
  • To explore the potential of multi-agent modeling for creating multi-scale biological systems.

Main Methods:

  • Utilizing multi-agent modeling as a design framework.
  • Applying the framework to case studies in synthetic ecologies, biological computation, and synthetic cellularity.
  • Analyzing complex multi-scale systems to identify underlying mechanisms.

Main Results:

  • Multi-agent modeling captures core features of complex multi-scale biological systems.
  • The approach provides insights into mechanisms guiding emergent functionalities across scales.
  • Identified design rules for engineering collective behaviors.

Conclusions:

  • Multi-agent modeling offers a pathway to overcome challenges in engineering emergent collective functions.
  • This framework facilitates the design of synthetic biology systems beyond single components.
  • Enables the creation of systems with functions emerging from multi-scale collectives.