Parameter extraction from single cell dynamics using numerical optimization techniques

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Abstract/Contents

Abstract
Cell signaling networks are complex dynamical systems with mechanisms for adaptation and failure-tolerance such that typical stimulus experiments are often robust to the perturbation of individual components. While such robustness is often advantageous, it also means that the information content of an experiment with respect to internal states and activities is often poor. We treat this problem formally by examining the statistical uncertainty of parameter estimates of corresponding signaling models as a function of experimental protocols that are based on live-cell imaging of fluorescent reporters. The first part of this work uses such model predictions of parameter sensitivity to design numerically optimized live-cell imaging protocols with the goal to maximally constrain the space of possible parameter values. The second part instead uses an experimental approach to define invariant parameters by correlated population estimates in order to reveal changes of regulated parameters in systematic siRNA perturbation experiments. Our results show that the effects of siRNA perturbations on reporter dynamics can be used to infer functional changes of the probed system. We exploit this feature to define not only the key molecules responsible for activity but also direct and indirect regulators.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2012
Issuance monographic
Language English

Creators/Contributors

Associated with Bandara, Samuel
Associated with Stanford University, Department of Chemical and Systems Biology.
Primary advisor Meyer, Tobias
Thesis advisor Meyer, Tobias
Thesis advisor Covert, Markus
Thesis advisor Dolmetsch, Ricardo E
Thesis advisor Ferrell, James Ellsworth
Advisor Covert, Markus
Advisor Dolmetsch, Ricardo E
Advisor Ferrell, James Ellsworth

Subjects

Genre Theses

Bibliographic information

Statement of responsibility Samuel Bandara.
Note Submitted to the Department of Chemical and Systems Biology.
Thesis Ph.D. Stanford University 2012
Location electronic resource

Access conditions

Copyright
© 2012 by Samuel Bandara

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