Chapter title |
Integrating fluorescent biosensor data using computational models.
|
---|---|
Chapter number | 18 |
Book title |
Fluorescent Protein-Based Biosensors
|
Published in |
Methods in molecular biology, January 2014
|
DOI | 10.1007/978-1-62703-622-1_18 |
Pubmed ID | |
Book ISBNs |
978-1-62703-621-4, 978-1-62703-622-1
|
Authors |
Eric C Greenwald, Renata K Polanowska-Grabowska, Jeffrey J Saucerman, Eric C. Greenwald, Renata K. Polanowska-Grabowska, Jeffrey J. Saucerman, Greenwald, Eric C., Polanowska-Grabowska, Renata K., Saucerman, Jeffrey J. |
Abstract |
This book chapter provides a tutorial on how to construct computational models of signaling networks for the integration and interpretation of FRET-based biosensor data. A model of cAMP production and PKA activation is presented to provide an example of the model building process. The computational model is defined using hypothesized signaling network structure and measured kinetic parameters and then simulated in Virtual Cell software. Experimental acquisition and processing of FRET biosensor data is discussed in the context of model validation. This data is then used to fit parameters of the computational model such that the model can more accurately predict experimental data. Finally, this model is used to show how computational experiments can interrogate signaling networks and provide testable hypotheses. This simple, yet detailed, tutorial on how to use computational models provides biologists that use biosensors a powerful tool to further probe and evaluate the underpinnings of a biological response. |
X Demographics
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Hungary | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 10 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Professor > Associate Professor | 3 | 30% |
Student > Ph. D. Student | 2 | 20% |
Researcher | 1 | 10% |
Student > Doctoral Student | 1 | 10% |
Unknown | 3 | 30% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 4 | 40% |
Biochemistry, Genetics and Molecular Biology | 1 | 10% |
Physics and Astronomy | 1 | 10% |
Medicine and Dentistry | 1 | 10% |
Unknown | 3 | 30% |