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[Emergence and biological complexity].

Jacques Ricard¹

¹Institut Jacques Monod, CNRS, Universités Paris 6 et Paris 7.

Journal De La Societe De Biologie

|June 2, 2006

Summary

Biological network organization determines information potential. Negative mutual information of integration indicates emergent complexity and novel functions, as seen in enzyme catalysis.

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Area of Science:

Systems biology
Information theory
Biophysics

Context:

Biological networks exhibit organizational principles that dictate their information processing capabilities.
Understanding system organization is crucial for deciphering emergent properties and functions.

Purpose:

To quantitatively define and differentiate three types of biological network organization using mutual information of integration (I(X:Y)N).
To establish criteria for identifying systems with emergent collective properties and novel functions.

Summary:

Mutual information of integration (I(X:Y)N) quantifies network organization.
I(X:Y)N = 0 indicates a mere collection of subsystems.
I(X:Y)N > 0 signifies integration without significant collective properties.
I(X:Y)N < 0 denotes complex systems with emergent properties, unpredictable from subsystems alone.

Impact:

This framework allows for the identification of complex biological systems and their emergent functions.
Provides a quantitative basis for understanding enzyme catalysis as an emergent property of protein-ligand interactions.
Facilitates the study of novel functions arising from specific network organizations in biological systems.

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