Discrete Dynamic Modeling with Asynchronous Update, or How to Model Complex Systems in the Absence of Quantitative Information

  • Sarah M. Assmann
  • Réka Albert
Part of the Methods in Molecular Biology™ book series (MIMB, volume 553)


A major aim of systems biology is the study of the inter-relationships found within and between large biological data sets. Here we describe one systems biology method, in which the tools of network analysis and discrete dynamic (Boolean) modeling are used to develop predictive models of cellular signaling in cases where detailed temporal and kinetic information regarding the propagation of the signal through the system is lacking. This approach is also applicable to data sets derived from some other types of biological systems, such as transcription factor-mediated regulation of gene expression during the control of developmental fate, or host defense responses following pathogen attack, and is equally applicable to plant and non-plant systems. The method also allows prediction of how elimination of one or more individual signaling components will affect the ultimate outcome, thus allowing the researcher to model the effects of genetic knockout or pharmacological block. The method also serves as a starting point from which more quantitative models can be developed as additional information becomes available.

Key words

Boolean model computational biology dynamic modeling discrete model network analysis signal transduction systems biology 


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Copyright information

© Humana Press, a part of Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Sarah M. Assmann
    • 1
  • Réka Albert
    • 2
  1. 1.Biology DepartmentPenn State UniversityUniversity ParkUSA
  2. 2.Physics DepartmentPenn State UniversityUniversity ParkUSA

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