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Processing of raw ratiometric biosensor images (for example based on FRET) into fully corrected "ratio maps" or "activation maps" — images showing the localized activation of the biosensor.

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u-probe 3.2

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Introduction

This MATLAB software package allows processing of raw ratiometric biosensor images (for example based on FRET) into fully corrected "ratio maps" or "activation maps" — images showing the localized activation of the biosensor. This includes application of all necessary image corrections needed for quantitative widefield imaging of ratiometric biosensors.

For more information, please see Biosensors for characterizing the dynamics of rho family GTPases in living cells, Curr Protoc Cell Biol, 2010, Chapter 14:Unit 14.11.1-26, written by Louis Hodgson, Feimo Shen, Klaus Hahn.

Documentation

Detailed instructions for how to download and load the u-probe package into MATLAB is provided via the Wiki tab that is located at the top of this GitHub repository.

Comprehensive descriptions of the u-probe package and its individual steps are available on the Wiki tab as well.

Software Feedback

Please submit any feedback on this package, including bugs and feature requests, via the Issues tab that is located at the top of this GitHub repository. General instruction on how to create an issue on GitHub can be found here.

Version History

New in Version 3.2:

  • Renamed the software package from Biosensor to u-probe. Please select u-probe from the analysis packages list to run the software.

New in Version 3.1:

  • Added a step to crop a ROI for segementation and its following steps.

New in Version 2.1:

  • Added support for movie relocation
  • Implemented a graphical interface for preparing data
  • Added a preview option when manually thresholding channels
  • Added graphical interfaces for the transformation creation and bleedthrough coefficients calculation
  • Included the ratio movie creation within the output process
  • Fixed various bugs (correction image display...)

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Processing of raw ratiometric biosensor images (for example based on FRET) into fully corrected "ratio maps" or "activation maps" — images showing the localized activation of the biosensor.

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