Systems Biology for Signaling Networks

  • Helikar T
  • Kochi N
  • Konvalina J
  • et al.
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Abstract

In this chapter we introduce a five-step modeling pipeline that ultimately leads to a mathematical description of a biochemical reaction system. We discuss how to automate each single step and how to put these steps together: First, we have to create a topology of interconversion processes and mutual influences between reactive species. An automated modeling procedure requires an appropriate data format that encodes the model in a computer-readable form. A standard like the Systems Biology Markup Language (SBML) serves this purpose and allows us to add semantic information to each component of the model. Second, from such an annotated network the procedure SBMLsqueezer generates kinetic equations in a context sensitive manner. The resulting model can then be combined with already existing models. Third, we estimate the values of all newly introduced parameters in each created rate law. This procedure requires a time series of quantitative measurements of the reactive species within this system to be available, because we calibrate the parameters with the aim that the model will fit these experimental data. Fourth, an experimental validation of the resulting model is advisable. Finally, a model report should be generated to document the model with all of its components. For a better understanding, we start our consideration with an introduction into necessary standardization attempts in today's systems biology and generalized approaches for common rate equations before we discuss the computer-aided modeling, parameter estimation, and automatic report generation. We complete this chapter with a discussion on possible further improvements of our modeling pipeline.

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Helikar, T., Kochi, N., Konvalina, J., & Rogers, J. A. (2010). Systems Biology for Signaling Networks. (S. Choi, Ed.), Systems Biology (pp. 295–336). New York, NY: Springer New York. https://doi.org/10.1007/978-1-4419-5797-9

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