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Fluorescent Protein-Based Biosensors

Overview of attention for book
Cover of 'Fluorescent Protein-Based Biosensors'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 The Design and Application of Genetically Encodable Biosensors Based on Fluorescent Proteins
  3. Altmetric Badge
    Chapter 2 An Introduction to Fluorescence Imaging Techniques Geared Towards Biosensor Applications
  4. Altmetric Badge
    Chapter 3 Fluorescent Protein-Based Biosensors
  5. Altmetric Badge
    Chapter 4 Detecting cAMP with an Epac-Based FRET Sensor in Single Living Cells
  6. Altmetric Badge
    Chapter 5 Analysis of Compartmentalized cAMP: A Method to Compare Signals from Differently Targeted FRET Reporters
  7. Altmetric Badge
    Chapter 6 Genetically Encoded Fluorescent Biosensors for Live Cell Imaging of Lipid Dynamics
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    Chapter 7 Live-Cell Imaging of Cytosolic NADH–NAD + Redox State Using a Genetically Encoded Fluorescent Biosensor
  9. Altmetric Badge
    Chapter 8 Measuring Membrane Voltage with Microbial Rhodopsins
  10. Altmetric Badge
    Chapter 9 Imaging the Activity of Ras Superfamily GTPase Proteins in Small Subcellular Compartments in Neurons
  11. Altmetric Badge
    Chapter 10 Imaging Kinase Activity at Protein Scaffolds
  12. Altmetric Badge
    Chapter 11 Using a Genetically Encoded FRET-Based Reporter to Visualize Calcineurin Phosphatase Activity in Living Cells
  13. Altmetric Badge
    Chapter 12 Genetically Encoded FRET Indicators for Live-Cell Imaging of Histone Acetylation.
  14. Altmetric Badge
    Chapter 13 Genetically Encoded Fluorescent Biosensors for Live-Cell Imaging of MT1-MMP Protease Activity.
  15. Altmetric Badge
    Chapter 14 Biosensor imaging in brain slice preparations.
  16. Altmetric Badge
    Chapter 15 Optical Calcium Imaging Using DNA-Encoded Fluorescence Sensors in Transgenic Fruit Flies, Drosophila melanogaster.
  17. Altmetric Badge
    Chapter 16 A Multiparameter Live Cell Imaging Approach to Monitor Cyclic AMP and Protein Kinase A Dynamics in Parallel
  18. Altmetric Badge
    Chapter 17 FRET and BRET-Based Biosensors in Live Cell Compound Screens.
  19. Altmetric Badge
    Chapter 18 Integrating fluorescent biosensor data using computational models.
Attention for Chapter 18: Integrating fluorescent biosensor data using computational models.
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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

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
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 %
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%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 September 2013.
All research outputs
#18,348,542
of 22,723,682 outputs
Outputs from Methods in molecular biology
#7,857
of 13,084 outputs
Outputs of similar age
#229,256
of 305,150 outputs
Outputs of similar age from Methods in molecular biology
#293
of 594 outputs
Altmetric has tracked 22,723,682 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,084 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 305,150 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 594 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.