Mean-field Boolean network model of a signal transduction network

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

In this paper we provide a mean-field Boolean network model for a signal transduction network of a generic fibroblast cell. The network consists of several main signaling pathways, including the receptor tyrosine kinase, the G-protein coupled receptor, and the Integrin signaling pathway. The network consists of 130 nodes, each representing a signaling molecule (mainly proteins). Nodes are governed by Boolean dynamics including canalizing functions as well as totalistic Boolean functions that depend only on the overall fraction of active nodes. We categorize the Boolean functions into several different classes. Using a mean-field approach we generate a mathematical formula for the probability of a node becoming active at any time step. The model is shown to be a good match for the actual network. This is done by iterating both the actual network and the model and comparing the results numerically. Using the Boolean model it is shown that the system is stable under a variety of parameter combinations. It is also shown that this model is suitable for assessing the dynamics of the network under protein mutations. Analytical results support the numerical observations that in the long-run at most half of the nodes of the network are active.

Original languageEnglish (US)
Pages (from-to)14-27
Number of pages14
JournalBioSystems
Volume108
Issue number1-3
DOIs
StatePublished - Apr 1 2012

Fingerprint

Boolean Model
Boolean Networks
Signal transduction
Signal Transduction
Mean Field
Network Model
Receptor Protein-Tyrosine Kinases
G-Protein-Coupled Receptors
Integrins
Boolean functions
Proteins
Fibroblasts
Vertex of a graph
Signaling Pathways
Mutation
G-Protein-Coupled Receptor Kinases
Boolean Functions
Receptor
Active networks
Integrin

Keywords

  • Bifurcations
  • Canalizing functions
  • Mean-field approximation
  • Mutations
  • Noise
  • Signal transduction network
  • Simulations
  • Stability

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Applied Mathematics

Cite this

Mean-field Boolean network model of a signal transduction network. / Kochi, Naomi; Matache, Mihaela Teodora.

In: BioSystems, Vol. 108, No. 1-3, 01.04.2012, p. 14-27.

Research output: Contribution to journalArticle

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