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

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5 tweeters
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1 patent

Citations

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4 Dimensions

Readers on

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175 Mendeley
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Title
Fluorescent Protein-Based Biosensors
Published by
Humana Press, September 2013
DOI 10.1007/978-1-62703-622-1
ISBNs
978-1-62703-621-4, 978-1-62703-622-1
Editors

Zhang, Jin, Ni, Qiang, Newman, Robert H

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 175 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
Australia 2 1%
Italy 1 <1%
France 1 <1%
Canada 1 <1%
Portugal 1 <1%
Unknown 166 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 57 33%
Researcher 51 29%
Student > Master 14 8%
Student > Bachelor 10 6%
Professor > Associate Professor 8 5%
Other 27 15%
Unknown 8 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 80 46%
Biochemistry, Genetics and Molecular Biology 30 17%
Chemistry 15 9%
Medicine and Dentistry 11 6%
Neuroscience 9 5%
Other 21 12%
Unknown 9 5%