42 Citations (Scopus)

Abstract

Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

Original languageEnglish (US)
Pages (from-to)281-306
Number of pages26
JournalMethods in enzymology
Volume467
Issue numberC
DOIs
StatePublished - Dec 14 2009

Fingerprint

Cell signaling
Signal transduction
Signal Transduction
Dynamic models
Cytology
Systems Biology
Electric network analysis
Molecular Structure
Kinetic parameters
Linear systems
Cell Biology
Theoretical Models
Mathematical models
Kinetics
Experiments

All Science Journal Classification (ASJC) codes

  • Biochemistry
  • Molecular Biology

Cite this

Albert, Reka Z. ; Wang, Rui Sheng. / Discrete Dynamic Modeling of Cellular Signaling Networks. In: Methods in enzymology. 2009 ; Vol. 467, No. C. pp. 281-306.
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Discrete Dynamic Modeling of Cellular Signaling Networks. / Albert, Reka Z.; Wang, Rui Sheng.

In: Methods in enzymology, Vol. 467, No. C, 14.12.2009, p. 281-306.

Research output: Contribution to journalReview article

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T1 - Discrete Dynamic Modeling of Cellular Signaling Networks

AU - Albert, Reka Z.

AU - Wang, Rui Sheng

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N2 - Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

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