Machine learning classification of trajectories from molecular dynamics simulations of chromosome segregation.

ABSTRACT: In contrast to the well characterized mitotic machinery in eukaryotes it seems as if there is no universal mechanism organizing chromosome segregation in all bacteria. Apparently, some bacteria even use combinations of different segregation mechanisms such as protein machines or rely on physical forces. The identification of the relevant mechanisms is a difficult task. Here, we introduce a new machine learning approach to this problem. It is based on the analysis of trajectories of individual loci in the course of chromosomal segregation obtained by fluorescence microscopy. While machine learning approaches have already been applied successfully to trajectory classification in other areas, so far it has not been possible to use them to discriminate segregation mechanisms in bacteria. A mai

SUBMITTER: Geisel D 

PROVIDER: S-EPMC8782305 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature