Using computational modeling and experimental synthetic perturbations to probe biological circuits

Joshua R. Porter, Eric Batchelor

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


This chapter describes approaches for using computational modeling of synthetic biology perturbations to analyze endogenous biological circuits, with a particular focus on signaling and metabolic pathways. We describe a bottom-up approach in which ordinary differential equations are constructed to model the core interactions of a pathway of interest. We then discuss methods for modeling synthetic perturbations that can be used to investigate properties of the natural circuit. Keeping in mind the importance of the interplay between modeling and experimentation, we next describe experimental methods for constructing synthetic perturbations to test the computational predictions. Finally, we present a case study of the p53 tumorsuppressor pathway, illustrating the process of modeling the core network, designing informative synthetic perturbations in silico, and testing the predictions in vivo.

Original languageEnglish (US)
Pages (from-to)259-276
Number of pages18
JournalMethods in Molecular Biology
StatePublished - 2015
Externally publishedYes


  • Computational modeling
  • Dynamical systems
  • Experimental design
  • Metabolism
  • Signal transduction
  • Synthetic biology

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