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Additionally, soTILT3D leverages computational tools such as deep learning for analysis of higher fluorophore concentrations for improved imaging speed and algorithms for real-time drift correction, enabling stable, high-precision imaging over extended periods of time.

If the ssDNA is cut up, the fluorophore and quencher move further apart.

They also identified two red fluorescent proteins that switch at different rates, and engineered one additional red fluorophore.

The mathematical technique that the researchers used to analyze the fluorophore signals is known as linear unmixing.

After imaging the cell for several minutes, hours, or even days, the researchers use a computational algorithm to pick out the specific signal from each fluorophore, analogous to how the human ear can pick out different frequencies of sound.