Identifying small pulsatile signals within noisy data: a fluorescence application

在噪声数据中识别微弱脉冲信号:荧光应用

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Abstract

One of the most challenging scientific data analysis quandaries is the identification of small intermittent irregularly spaced pulsatile signals in the presence of large amounts of heteroscedastic experimental measurement uncertainties. We present an application of the use of AutoDecon to a typical fluorescence and/or spectroscopic data sampling paradigm, which is to detect a single fluorophore in the presence of high background emission. Our calculations demonstrate that single events can be reliably detected by AutoDecon with a signal-to-noise ratio of 3/20. AutoDecon was originally developed for the analysis of pulsatile hormone-concentration time-series data measured in human serum. However, AutoDecon has applications within many other scientific fields, such as fluorescence measurements where the goal is to count single analyte molecules in clinical samples.

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