What is it about?

Flow cytometry is a powerful tool for identifying and quantifying various cell markers, such as viability, vitality, and individual cell age, at single-cell stages. However, cell autofluorescence and marker fluorophore signals overlap at low fluorescence intensities. Thus, these signals must be unmixed before determining the age fraction.

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Why is it important?

In living organisms, autofluorescence overlaps with the fluorophore signals, making flow cytometric data analysis challenging. For this purpose, the principal component regression and an RF model were compared concerning the prediction of autofluorescence signals.


The demonstrated approach enables fast and reliable unmixing of flow cytometric spectral data using a single-laser spectral unmixing method. This analysis method enables age determination of cells in industrial processes. This age determination allows for quantifying the yeast cell's age fractions, providing a detailed view of age-related changes.

Marco Eigenfeld
Technische Universität München

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This page is a summary of: Autofluorescence prediction model for fluorescence unmixing and age determination, Biotechnology Journal, November 2022, Wiley, DOI: 10.1002/biot.202200091.
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