Jacques Pécréaux

This study shows that ZYG-8 increases microtubule rigidity, which is essential for proper spindle orientation during C. elegans zygote division, and links microtubule mechanics to spindle positioning.

The paper introduces a semi-supervised GAN for cell cycle classification using limited annotated data and unlabelled microscopy images, achieving high accuracy on the Mitocheck dataset.

The Roboscope autonomously captures rare biological events using deep learning and sequence interruption, demonstrating efficiency with minimal training data.

The paper identifies three archetypes of spindle elongation in C. elegans embryos that capture most inter-individual variability, revealing that only three independent mechanisms drive spindle elongation across conditions.

The paper develops a fast image classification method for biological microscopy by selecting discriminant features and using machine learning to improve speed and accuracy.

The paper shows that LET-99 restricts force generators to a posterior crescent, making spindle positioning robust despite variations in force generator numbers.

The paper investigates dynein dynamics during C. elegans zygote division, finding that dynein accumulates at microtubule plus-ends and cortex, with posterior enrichment contributing to force imbalance and polarity.