Rasa Elmentaite

Human Developmental Cell Atlas integrates ~4.6 million cells/nuclei from 4-22 post-conception weeks into 454 refined cell types and maps 114 spatial niches across 6PCW whole-embryo sections.

This paper develops a continual learning framework to map colorectal cancer cell states to causal mechanisms through integration of single-cell data and perturbation experiments.

The paper creates a regulon atlas mapping TF activity across human cell types and uses it to link disease signatures to cell types and TFs, improving disease risk locus analysis.

The paper integrates single-cell RNA-seq datasets across the GI tract to identify epithelial metaplasia in inflammatory diseases, showing its role in inflammation through immune cell interactions.

This study investigates how scRNA-seq data can predict the clinical success of drug targets by analyzing cell type and disease-specific expression patterns.

This paper creates a human embryonic limb cell atlas using single-cell and spatial transcriptomics, identifying novel cell populations and developmental patterns.

cell2location uses a Bayesian model to integrate single-cell and spatial transcriptomics, mapping cell types in situ across mouse brain regions and human lymph node immune compartments.

This paper introduces a minimized double guide RNA library for CRISPR/Cas9 screens, reducing scale by fivefold while maintaining performance.