Richard C. V. Tyser

The paper investigates the role of calcium signaling in anterior-posterior axis formation in the mouse embryo, finding that SERCA inhibition disrupts DVE migration and axial patterning.

The paper identifies enhancers regulating Chd7 expression in neural crest cells and validates their function in chick embryos, revealing tissue-specific regulation of a chromatin remodeller.

This study develops a multi-omic reference of human cardiac development and identifies disruptions in Trisomy 21 hearts.

The paper creates a high-resolution human developing heart atlas using single-cell and spatial transcriptomics, identifies new cell types, and benchmarks in vitro models.

The paper develops statistical tools to analyze gene knockouts in mouse embryos and applies them to study developmental disruptions and cancer therapy responses.

This study identifies asymmetrically expressed genes in the mouse cardiac crescent during left-right symmetry breaking using single-cell RNA sequencing and validates their expression patterns.

CIARA identifies markers of rare cell types from single-cell RNA-seq data, outperforming existing methods and discovering new cell populations in mouse and human samples.

SageNet predicts spatial positions and cell-cell proximities of dissociated single-cell data using a graph neural network trained on spatial references.

This paper presents a spatially resolved single-cell transcriptome atlas of human gastrulation, identifying novel cell types and revealing key differences from mouse gastrulation.

This paper uses spatial transcriptomics to study mouse organogenesis, revealing spatial gene expression patterns and cell fate decisions not captured by single-cell RNA sequencing.

The paper introduces SilentMark, a lightweight image analysis tool for spatial protein analysis in mammalian tissues, capable of handling noisy and crowded images and providing geometry-based quantification.