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Design of Experiments to Investigate Dynamic Cell Signaling Models

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Computational Modeling of Signaling Networks

Part of the book series: Methods in Molecular Biology ((MIMB,volume 880))

Abstract

This chapter describes approaches to make use of dynamic models of cell signaling systems in order to optimize experiments in cell biology. We are particularly focusing on the question of how small molecule inhibitors or activators can best be used to get the most information out of a limited number of experiments when only a handful of molecular species can be measured. One goal addressed by this chapter is to find time course experiments to discriminate between rivaling molecular mechanisms. The other goal is to find experiments that are useful for inferring rate constants, binding affinities, concentrations, and other model parameters from time course data. Both are treated as optimal control problems in which rapid pharmacological perturbation schemes are identified in silico in order to close an experimental cycle from modeling back to the laboratory bench.

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Acknowledgements

We would like to thank Johannes Schlöder, Sean Collins, Meredith Betterton, and Xuedong Liu for helpful comments on this chapter.

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Correspondence to Samuel Bandara .

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© 2012 Springer Science+Business Media, LLC

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Bandara, S., Meyer, T. (2012). Design of Experiments to Investigate Dynamic Cell Signaling Models. In: Liu, X., Betterton, M. (eds) Computational Modeling of Signaling Networks. Methods in Molecular Biology, vol 880. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-61779-833-7_7

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  • DOI: https://doi.org/10.1007/978-1-61779-833-7_7

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  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-61779-832-0

  • Online ISBN: 978-1-61779-833-7

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