On the reliability of fluorescence decay data

Hinde, A.L.; Selinger, BK; Nott, PR

doi:10.1071/ch9772383

Cited by 15 publications

(6 citation statements)

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“…The method of convolution used here has been shown to be the most successful of seven deconvolution techniques32 and the reliability of such an analysis has been discussed. 33 The lifetime results reported here are the mean and 95% confidence interval of at least six determinations.…”

Section: Discussionmentioning

confidence: 99%

Proton-induced fluorescence quenching of 2-naphthol

Harris¹,

Selinger²

1980

J. Phys. Chem.

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Section: Discussionmentioning

confidence: 99%

Proton-induced fluorescence quenching of 2-naphthol

Harris¹,

Selinger²

1980

J. Phys. Chem.

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“…1024 1024 (17) We can define a likelihood function as the joint probability density function above: ( , ) = ( 1 , 2 , ⋯ , 1024 ). We substitute the expression for the probability as =̂/ to obtain:…”

Section: Maximum Likelihood Methods (Ml)mentioning

confidence: 99%

“…There are several comparisons of the ML and RM techniques, − but most of them have been limited to simulated data. In those cases where the techniques were applied to real experimental data, the comparisons were limited by several factors such as the exclusion of a real instrument response function (IRF), the bin size for the time channels of the histogram, the exclusion of a shift parameter that accounts for the wavelength difference between the instrument response function and the fluorescence signal, and, most importantly, not determining the minimum number of counts at which the respective techniques provide an acceptable result.…”

Section: Introductionmentioning

confidence: 99%

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Photon Counting Data Analysis: Application of the Maximum Likelihood and Related Methods for the Determination of Lifetimes in Mixtures of Rose Bengal and Rhodamine B

et al. 2016

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It is often convenient to know the minimum amount of data needed to obtain a result of desired accuracy and precision. It is a necessity in the case of subdiffraction-limited microscopies, such as stimulated emission depletion (STED) microscopy, owing to the limited sample volumes and the extreme sensitivity of the samples to photobleaching and photodamage. We present a detailed comparison of probability-based techniques (the maximum likelihood method and methods based on the binomial and the Poisson distributions) with residual minimization-based techniques for retrieving the fluorescence decay parameters for various two-fluorophore mixtures, as a function of the total number of photon counts, in time-correlated, single-photon counting experiments. The probability-based techniques proved to be the most robust (insensitive to initial values) in retrieving the target parameters and, in fact, performed equivalently to 2-3 significant figures. This is to be expected, as we demonstrate that the three methods are fundamentally related. Furthermore, methods based on the Poisson and binomial distributions have the desirable feature of providing a bin-by-bin analysis of a single fluorescence decay trace, which thus permits statistics to be acquired using only the one trace not only for the mean and median values of the fluorescence decay parameters but also for the associated standard deviations. These probability-based methods lend themselves well to the analysis of the sparse data sets that are encountered in subdiffraction-limited microscopies. Disciplines Chemistry | Physical Chemistry CommentsThis document is the unedited Author's version of a Submitted Work that was subsequently accepted for publication as Santra, Kalyan, Emily A. Smith, Jacob W. Petrich, and Xueyu Song. ABSTRACTIt is often convenient to know the minimum amount of data needed in order to obtain a result of desired accuracy and precision. It is a necessity in the case of subdiffraction-limited microscopies, such as stimulated emission depletion (STED) microscopy, owing to the limited sample volumes and the extreme sensitivity of the samples to photobleaching and photodamage.We present a detailed comparison of probability-based techniques (the maximum likelihood method and methods based on the binomial and the Poisson distributions) with residual minimization-based techniques for retrieving the fluorescence decay parameters for various twofluorophore mixtures, as a function of the total number of photon counts, in time-correlated, singlephoton counting experiments. The probability-based techniques proved to be the most robust (insensitive to initial values) in retrieving the target parameters and, in fact, performed equivalently to 2-3 significant figures. This is to be expected, as we demonstrate that the three methods are fundamentally related. Furthermore, methods based on the Poisson and binomial distributions have the desirable feature of providing a bin-by-bin analysis of a single fluorescence decay trace, which thus permits statistic...

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“…Analyzing data via RM and ML methods has, of course, been previously discussed. ,− With a few exceptions, ,,, these analyses were limited to simulated data. Our work has been stimulated by the efforts of Maus et al, who provided a careful and detailed comparison of the RM (to which they refer as LS, “least squares”) and ML methods using experimental data.…”

Section: Introductionmentioning

confidence: 99%

What Is the Best Method to Fit Time-Resolved Data? A Comparison of the Residual Minimization and the Maximum Likelihood Techniques As Applied to Experimental Time-Correlated, Single-Photon Counting Data

et al. 2016

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The need for measuring fluorescence lifetimes of species in subdiffraction-limited volumes in, for example, stimulated emission depletion (STED) microscopy, entails the dual challenge of probing a small number of fluorophores and fitting the concomitant sparse data set to the appropriate excited-state decay function. This need has stimulated a further investigation into the relative merits of two fitting techniques commonly referred to as "residual minimization" (RM) and "maximum likelihood" (ML). Fluorescence decays of the well-characterized standard, rose bengal in methanol at room temperature (530 ± 10 ps), were acquired in a set of five experiments in which the total number of "photon counts" was approximately 20, 200, 1000, 3000, and 6000 and there were about 2-200 counts at the maxima of the respective decays. Each set of experiments was repeated 50 times to generate the appropriate statistics. Each of the 250 data sets was analyzed by ML and two different RM methods (differing in the weighting of residuals) using in-house routines and compared with a frequently used commercial RM routine. Convolution with a real instrument response function was always included in the fitting. While RM using Pearson's weighting of residuals can recover the correct mean result with a total number of counts of 1000 or more, ML distinguishes itself by yielding, in all cases, the same mean lifetime within 2% of the accepted value. For 200 total counts and greater, ML always provides a standard deviation of <10% of the mean lifetime, and even at 20 total counts there is only 20% error in the mean lifetime. The robustness of ML advocates its use for sparse data sets such as those acquired in some subdiffraction-limited microscopies, such as STED, and, more importantly, provides greater motivation for exploiting the time-resolved capacities of this technique to acquire and analyze fluorescence lifetime data.

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On the reliability of fluorescence decay data

Cited by 15 publications

References 0 publications

Proton-induced fluorescence quenching of 2-naphthol

Proton-induced fluorescence quenching of 2-naphthol

Photon Counting Data Analysis: Application of the Maximum Likelihood and Related Methods for the Determination of Lifetimes in Mixtures of Rose Bengal and Rhodamine B

What Is the Best Method to Fit Time-Resolved Data? A Comparison of the Residual Minimization and the Maximum Likelihood Techniques As Applied to Experimental Time-Correlated, Single-Photon Counting Data

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