Sofia Kapsiani

The paper develops a hybrid machine learning framework to identify TDP-43 aggregation inhibitors, discovering two compounds effective in reducing aggregation in cell and model organism assays.

FLIMngo, a deep learning model, enables fast and accurate fluorescence lifetime predictions from low-photon FLIM data, improving throughput and reducing phototoxicity for in vivo applications.

FLIMPA is an open-source software for FLIM phasor analysis that integrates data from multiple trials and provides tools for quantifying microtubule depolymerisation.