Characterizing cellular receptor dynamics in live fluorescence imaging using stochastic modeling and machine learning
Giacomo Nardi, Matheus Santos Sano, Margaux Bilay, Anne Brelot, Jean-Christophe Olivo-Marin, Thibault Lagache · 2026
Read Characterizing cellular receptor dynamics in live fluorescence imaging using stochastic modeling and machine learning by Giacomo Nardi, Matheus Santos Sano, Margaux Bilay, Anne Brelot, Jean-Christophe Olivo-Marin, Thibault Lagache (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13571939.txt.
Description
Cell surface catchers wander in patterns that betray their state, and Giacomo Nardi and co-authors teach a program to read those patterns live, in work from twenty twenty-six. Single-particle tracks from a surface-only microscope feed the system. Shape traits of each track join a forest classifier that sorts five motion kinds.
Run on a virus co-catcher, the method caught a drug-driven shift: free, stop-start wandering gave way to penned, pulled-in motion, as expected when catchers cluster and get swallowed. The traits stay readable, so biologists see why a call was made. The frame suits any membrane protein tracked the same way.
Catalog record
| CREATOR | Giacomo Nardi, Matheus Santos Sano, Margaux Bilay, Anne Brelot, Jean-Christophe Olivo-Marin, Thibault Lagache |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 73 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |