TY  - JOUR
A1  - Malkusch, Sebastian
A1  - Rahm, Johanna V.
A1  - Dietz, Marina
A1  - Heilemann, Mike
A1  - Sibarita, Jean-Baptiste
A1  - Lötsch, Jörn
T1  - Receptor tyrosine kinase MET ligand-interaction classified via machine learning from single-particle tracking data
T2  - Molecular Biology of the Cell
N2  - Internalin B–mediated activation of the membrane-bound receptor tyrosine kinase MET is accompanied by a change in receptor mobility. Conversely, it should be possible to infer from receptor mobility whether a cell has been treated with internalin B. Here, we propose a method based on hidden Markov modeling and explainable artificial intelligence that machine-learns the key differences in MET mobility between internalin B–treated and –untreated cells from single-particle tracking data. Our method assigns receptor mobility to three diffusion modes (immobile, slow, and fast). It discriminates between internalin B–treated and –untreated cells with a balanced accuracy of >99% and identifies three parameters that are most affected by internalin B treatment: a decrease in the mobility of slow molecules (1) and a depopulation of the fast mode (2) caused by an increased transition of fast molecules to the slow mode (3). Our approach is based entirely on free software and is readily applicable to the analysis of other membrane receptors.
Y1  - 2022
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/75580
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-755808
VL  - 33
IS  - 6, ar60
ER  -