Jessica Ewald

Cell Painting and machine learning for mechanistic profiling of hepatotoxic botanicals and their constituents

This study uses Cell Painting and machine learning to identify hepatotoxic botanical constituents and their mechanisms in human hepatocytes.

Cell Painting for cytotoxicity and mode-of-action analysis in primary human hepatocytes

Cell Painting in primary human hepatocytes exposed to 1,085 compounds detects bioactivity at lower concentrations than cytotoxicity assays and predicts cell-based, but not cell-free, ToxCast endpoints across feature extractors.

A scalable approach to resolving variants of uncertain significance

The paper develops a scalable workflow to reclassify variants of uncertain significance using experimental and predictive evidence, resolving 75% of VUS in 40 genes.

Identifying and targeting abnormal mitochondrial localization associated with psychosis

The paper identifies a mitochondrial localization phenotype in psychosis patients and uses a cell-based assay to screen for compounds and genes affecting this phenotype.

Morphological map of under- and over-expression of genes in human cells

The paper presents a comprehensive genetic perturbation dataset using Cell Painting to analyze gene expression effects in human cells, revealing novel gene clusters and functional relationships.

Linking molecular pathways and islet cell dysfunction in human type 1 diabetes

This study investigates islet cell dysfunction in type 1 diabetes by integrating electrophysiological, transcriptomic, and machine learning analyses of human islet cells from T1D donors.

Evaluating batch correction methods for image-based cell profiling

The paper benchmarks seven scRNA-seq batch correction methods on a Cell Painting dataset, finding Harmony performs best across multiple scenarios.

HumanIslets: An integrated platform for human islet data access and analysis

HumanIslets.com provides an open platform for accessing and analyzing human islet data, enabling research on diabetes through integrated molecular and cellular phenotyping.