ArticleMethods in enzymology2013
Time-integrated fluorescence cumulant analysis and its application in living cells.
Article in Methods in enzymology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Principles of fluorescence correlation spectroscopy applied to studies of biomolecular liquid-liquid phase separation.Biophysics reports · 2022Article
- Combined FCS and PCH Analysis to Quantify Protein Dimerization in Living Cells.International journal of molecular sciences · 2021Article
- Advanced fluorescence microscopy methods for the real-time study of transcription and chromatin dynamics.Transcription · 2014Review
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Authors and funding
3 authors.
Funding
Abstract
Time-integrated fluorescence cumulant analysis (TIFCA) is a data analysis technique for fluorescence fluctuation spectroscopy (FFS) that extracts information from the cumulants of the integrated fluorescence intensity. It is the first exact theory that describes the effect of sampling time on FFS experiment. Rebinning of data to longer sampling times helps to increase the signal/noise ratio of the experimental cumulants of the photon counts. The sampling time dependence of the cumulants encodes both brightness and diffusion information of the sample. TIFCA analysis extracts this information by fitting the cumulants to model functions. Generalization of TIFCA to multicolor FFS experiment is straightforward. Here, we present an overview of the theory, its implementation, as well as the benefits and requirements of TIFCA. The questions of why, when, and how to use TIFCA will be discussed. We give several examples of practical applications of TIFCA, particularly focused on measuring molecular interaction in living cells.
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