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International Conference on Advanced Concepts for Intelligent Vision Systems

ACIVS 2016: Advanced Concepts for Intelligent Vision Systems pp 105–116Cite as

Intramolecular FRET Efficiency Measures for Time-Lapse Fluorescence Microscopy Images

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10016))

Abstract

Here we investigate quantitative measures of Förster resonance energy transfer (FRET) efficiency that can be used to quantify protein-protein interactions using fluorescence microscopy images of living cells. We adopt a joint intensity space approach and develop a parametric shot noise model to estimate the uncertainty of FRET efficiency on a per pixel basis. We evaluate our metrics rigorously by simulating photon emission events corresponding to typical conditions and demonstrate advantages of our metrics over the conventional ratiometric one. In particular, our measure is linear, normalised and has greater tolerance to low SNR characteristic of FRET fluorescence microscopy images.

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Acknowledgements

Supported by Platform for Dynamic Approaches to Living Systems from MEXT Japan.

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Authors and Affiliations

  1. Graduate School of Informatics, Kyoto University, Kyoto, Japan

    Mark Holden

Authors
  1. Mark Holden
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Correspondence to Mark Holden .

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Editors and Affiliations

  1. Université Paris-Sud 11 , Orsay, France

    Jacques Blanc-Talon

  2. University of Salento , Lecce, Lecce, Italy

    Cosimo Distante

  3. Ghent University , Gent, Belgium

    Wilfried Philips

  4. CSIRO ICT Centre , Sydney, New South Wales, Australia

    Dan Popescu

  5. University of Antwerp , Wilrijk, Belgium

    Paul Scheunders

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Holden, M. (2016). Intramolecular FRET Efficiency Measures for Time-Lapse Fluorescence Microscopy Images. In: Blanc-Talon, J., Distante, C., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2016. Lecture Notes in Computer Science(), vol 10016. Springer, Cham. https://doi.org/10.1007/978-3-319-48680-2_10

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  • DOI: https://doi.org/10.1007/978-3-319-48680-2_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48679-6

  • Online ISBN: 978-3-319-48680-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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