Michael A. Dyer

This paper develops an AI framework to interpret single-cell RNA-seq data from pediatric solid tumors, identifying tumor-specific surface antigen pairs for targeted therapies.

Crop-OCT is an automated pipeline for analyzing OCT images to identify retinopathy in murine models, enabling the detection of regional and focal lesions across multiple diseases.

The paper identifies distinct transcriptional programs in Ewing sarcoma driven by EWS::FLI1 fusions and shows their variability across tumors and cell lines.

The paper identifies glycerophospholipid biosynthesis upregulation as a mechanism of chemoresistance in SLFN11-loss Ewing sarcoma and shows that inhibiting this pathway enhances DNA-damaging agent efficacy.

The paper identifies 'pliancy genes' in Muller glia that enable rapid response to retinal stress, injury, and disease, showing species-specific differences in their activation between zebrafish and mammals.

The paper investigates RA's limited effect on primary neuroblastoma tumors but efficacy in clearing bone marrow cells, identifying BMP signaling as a key determinant of cell fate and RA sensitivity.

This study identifies PAX3-FOXO1 and PAX7-FOXO1 fusion proteins as drivers of mitochondrial translation gene networks in pediatric rhabdomyosarcoma, offering new therapeutic targets.

This study identifies therapy-resistant and tumor-acquired cell states in pediatric rhabdomyosarcoma using single-cell RNA sequencing.

This paper establishes a diverse collection of preclinical models for pediatric solid tumors and demonstrates their utility in precision medicine trials and drug testing.

This paper creates a spatial cell atlas of neuroblastoma, revealing tumor heterogeneity through multi-omics data and identifying spatial compartmentalization and signaling patterns.

The paper identifies evolutionarily conserved VSX2 enhancer modules in retinal development and shows their functional conservation across species.

This study uses scRNA-seq to analyze molecular maturation of mouse retinal ganglion cells, showing visual activity is not required for type identity but is needed for full maturation.

The paper develops a toolbox for scRNA-Seq and snRNA-Seq of fresh and frozen human tumors, testing it across eight tumor types and optimizing protocols for different tissue characteristics.

XenoCP is a cloud-based tool that removes mouse reads from xenograft BAM files to improve RNA-seq and WGS analysis accuracy.

The paper studies the chromatin structure of rod photoreceptors in mice using Hi-C and machine learning to identify regulatory elements involved in retinal development.