VNC-Dist: A machine learning-based semi-automated pipeline for quantification of neuronal position in the C. elegans ventral nerve cord.

ABSTRACT: The C. elegans ventral nerve cord (VNC) provides a genetically tractable model for investigating the developmental mechanisms involved in neuronal positioning and organization. The VNC of newly hatched larvae contains a set of 22 motoneurons organized into three distinct classes (DD, DA, and DB) that show consistent positioning and arrangement. This organization arises from the action of multiple convergent genetic pathways, which are poorly understood. To better understand these pathways, accurate and efficient methods for quantifying motoneuron cell body positions within large microscopy datasets are required. Here, we present VNC-Dist (Ventral Nerve Cord Distances), a software toolkit that replaces manual measurements with a faster and more accurate computer-assisted approach, combining

SUBMITTER: Saharkhiz S 

PROVIDER: S-EPMC12393719 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature