Accuracy and precision in quantitative fluorescence microscopy

By Jennifer Waters. Journal of Cell Biology, 2009

637 citations recorded by the source corpus.

The light microscope has long been used to document the localization of fluorescent molecules in cell biology research. With advances in digital cameras and the discovery and development of genetically encoded fluorophores, there has been a huge increase in the use of fluorescence microscopy to quantify spatial and temporal measurements of fluorescent molecules in biological specimens. Whether simply comparing the relative intensities of two fluorescent specimens, or using advanced techniques like Förster resonance energy transfer (FRET) or fluorescence recovery after photobleaching (FRAP), quantitation of fluorescence requires a thorough understanding of the limitations of and proper use of the different components of the imaging system. Here, I focus on the parameters of digital image acquisition that affect the accuracy and precision of quantitative fluorescence microscopy measurements.

Subfields: Biophysics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/2807ed15a4ec156e714e8688c07ca7ec7e2be5f6

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Citations in the corpus

Goals and practicalities of immunoblotting and immunohistochemistry: A guide for submission to the British Journal of Pharmacology (2018, background): “This is problematic when a sample is incubated with several fluorophores with overlapping excitation and emission profiles (Ploem, 1999; Bolte and Cordelieres, 2006; Rietdorf and Stelzer, 2006; Waters, 2009).”
Image analysis and machine learning for detecting malaria (2018, positive): “It has been shown that fluorochrome staining is more sensitive and less timeconsuming than Romanowsky and Giemsa staining methods(23-25) but requires considerable practice and training, and suffers from artifacts including photobleaching and phototoxicity.(26,27) Moreover, fluorescence microscopes a”
Large‐scale image‐based screening and profiling of cellular phenotypes (2017, methodology): “First, image pre-processing algorithms are used to reduce noise and correct non-even background or illumination in the images (66).”
Reproducibility: Designing a rigorous microscopy experiment: Validating methods and avoiding bias (2019, positive): “Images of different wavelengths (e.g., fluorescence channels) collected from the same sample will not align perfectly in XY or Z, due to differences between fluorescence filters (Waters, 2009) and/or chromatic aberration in lenses (Keller, 2006; Ross et al., 2014).”