Complexity of generic biochemical circuits: Topology versus strength of interactions

Mikhail Tikhonov, William Bialek

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

The historical focus on network topology as a determinant of biological function is still largely maintained today, illustrated by the rise of structure-only approaches to network analysis. However, biochemical circuits and genetic regulatory networks are defined both by their topology and by a multitude of continuously adjustable parameters, such as the strength of interactions between nodes, also recognized as important. Here we present a class of simple perceptron-based Boolean models within which comparing the relative importance of topology versus interaction strengths becomes a quantitatively well-posed problem. We quantify the intuition that for generic networks, optimization of interaction strengths is a crucial ingredient of achieving high complexity, defined here as the number of fixed points the network can accommodate. We propose a new methodology for characterizing the relative role of parameter optimization for topologies of a given class.

Original languageEnglish (US)
Article number066012
JournalPhysical Biology
Volume13
Issue number6
DOIs
StatePublished - Dec 5 2016

All Science Journal Classification (ASJC) codes

  • Biophysics
  • Structural Biology
  • Molecular Biology
  • Cell Biology

Keywords

  • Boolean networks
  • complexity
  • genetic networks

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