Abstract
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 language | English (US) |
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Pages (from-to) | 259-276 |
Number of pages | 18 |
Journal | Methods in Molecular Biology |
Volume | 1244 |
DOIs | |
State | Published - 2015 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© Springer Science+Business Media New York 2015.
Keywords
- Computational modeling
- Dynamical systems
- Experimental design
- Metabolism
- Signal transduction
- Synthetic biology