Lu-yan Chan

EmbSAM: Cell boundary localization and Segment Anything Model for fast images of developing embryos

EmbSAM provides a framework for 3D cell membrane segmentation in C. elegans embryos using deep learning and the Segment Anything Model, enabling analysis of cell shape dynamics during development.

Quantitative cell morphology in C. elegans embryos reveals regulations of cell volume asymmetry

The paper quantifies cell morphology in C. elegans embryos, revealing that signaling pathways regulate both cell fate asymmetry and volume asymmetry.

Highly efficient transgenesis with miniMos in Caenorhabditis briggsae

This paper improves transgenesis efficiency in C. briggsae by modifying a transposon-based method with a heat shock step, enabling single-copy insertions and applications in hybrid male sterility studies.

Genomic architecture of 5S rDNA cluster and its variations within and between species

The paper characterizes the genomic structure and variation of the 5S rDNA cluster in C. elegans and C. briggsae strains, revealing differences in stability and transcriptional compatibility.

Computable Early C. elegans Embryo with a Data-driven Phase Field Model

The paper develops a data-driven phase field model to simulate early C. elegans embryo morphogenesis using imaging data, revealing the roles of cell division and cell-cell attraction.

Establishment of morphological atlas of Caenorhabditis elegans embryo with cellular resolution using deep-learning-based 4D segmentation

The paper develops CShaper, a deep-learning-based pipeline to generate a 4D morphological atlas of C. elegans embryos, characterizing cell shape, migration, and cell-cell contacts across development.

System-Level Quantification and Phenotyping of Early Embryonic Morphogenesis of Caenorhabditis elegans

The paper quantifies and phenotypes early embryonic morphogenesis in C. elegans using a reference embryo and system-level phenotyping methods to analyze 1818 mutant embryos.