Monica M. Jablonski

This paper expands the RatGTEx resource with transcriptome-wide associations across 3,160 RNA-seq samples, identifying 7,473 gene-trait links and 144,876 QTLs for 22,599 genes.

This paper benchmarks automated nerve morphometry tools on mouse and rat optic nerve datasets, finding comparable performance between classical and deep learning methods.

This study characterizes the BXD51 mouse strain as a reproducible model of chronic progressive glaucoma, showing distinct clinical and structural features compared to other strains.

This study evaluates three deep learning models for optic nerve axon quantification on a novel rat dataset, finding reduced performance compared to published benchmarks.

MONICA is a web-based tool that automatically extracts optic nerve boundaries and calculates morphometric metrics, validated across species and image qualities.

The paper genotypes Y and mitochondrial chromosomes in heterogeneous stock rats and finds no significant associations with complex traits, except for gene expression on these chromosomes.

This study performs a GWAS in HS rats to identify genetic loci associated with intraocular pressure, finding three genome-wide significant loci and five candidate genes, including novel ones.

The paper presents two computational methods to reduce contamination in single-cell RNA-seq data, improving clustering and biological interpretation.