Variance Reducing and Noise Correction in Protein Quantification by Measuring Fluctuations in Fluorescence due to Photobleaching

Abstract

Quantifying protein number using the ratio between the variance and the mean of the protein distribution is a straightforward calibration method in the experimental conditions for microscopy imaging. Recently the model has been expanded to decaying processes with binomial distribution. In this paper, we examine the model proposed, and show how the algorithm can be adapted to the case of variance in the initial number of proteins between cells. We propose improving the algorithm so that the information processing of each frame is done independently from other frames. By doing so, the variance in the process of determining the protein number can be reduced. In addition, we examine the handling of unwanted noises in the measurement, offer a solution for shot noise and background noise, and examine the expected error caused in calculating the decay constant. We also analyze the expected difficulties in conducting a practical experiment, which includes non-exponential decay, and variance in the decay constants of the cells. These methods can be applied to any superposition of n0 discrete decaying processes. However, the evaluation of expected errors in quantification is essential for early planning of the experimental conditions, and for the evaluation of the error.