Classification of first embryonic division stages of multiple Caenorhabditis species by deep learning.

ABSTRACT: The first embryonic division of Caenorhabditis elegans is a model for asymmetric cell division, and identifying the stages of cell division across related species could improve our understanding of the divergence of cellular events and mechanisms. Comparative microscopy of evolutionarily divergent species continues to rely on label-free differential interference contrast (DIC) microscopy due to technical challenges in molecular tagging, with the identification of cell division stages still relying on label-free microscopy. Here, we compare multiple deep convolutional neural networks (CNNs) trained to automate cell stage classification in DIC microscopy movies and interpret the results, with code and classification weights released as OpenSource. The networks are trained to identify if a si

SUBMITTER: Khatri D 

PROVIDER: S-EPMC12375112 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature