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Related Experiment Videos

A diffuse biosemiotic model for cell-to-tissue computational closure.

R Cottam1, W Ranson, R Vounckx

  • 1The Evolutionary Processing Group (EVOL), Laboratory for Micro and Opto Electronics (LAMI), VUB Division of the Inter-University Micro Electronics Center (IMEC), The University of Brussels (VUB), Pleinlaan 2, 1050, Brussels, Belgium. evol@etro.vub.ac.be

Bio Systems
|April 4, 2000
PubMed
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This study introduces diffuse rationality, linking biosemiotics and computation for understanding life and consciousness. An evolutionary model explores scale-dependent autonomy and dependence in complex biological systems.

Area of Science:

  • Biophysics
  • Theoretical Biology
  • Computational Biology

Background:

  • Biological systems exhibit complexity at inter-scalar interfaces.
  • Understanding the emergence of life and consciousness requires bridging different scientific domains.

Purpose of the Study:

  • To propose diffuse rationality as a framework connecting biosemiotics and computation.
  • To develop an evolutionary model for scale-dependent autonomy and dependence.
  • To explore the complex-rational-complex dynamics in biological systems.

Main Methods:

  • Formulating local-to-global self-consistent criteria for cellular-to-tissue interfacing.
  • Developing an evolutionary model for inter-scalar relationships.
  • Analyzing the alternating complex-rational-complex nature of biological interactions.

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Main Results:

  • Diffuse rationality provides a bridge between biosemiotics and computation.
  • The evolutionary model elucidates the interplay of autonomy and dependence across biological scales.
  • The complex-rational-complex dynamic is identified as a key feature of biological interfaces.

Conclusions:

  • The proposed framework aids in understanding the emergence of life and consciousness.
  • The evolutionary model offers insights into biological complexity and self-organization.
  • Diffuse rationality is a promising concept for future research in theoretical and computational biology.