Virginia Savova

CellAtria automates scRNA-seq data ingestion and analysis through an AI agent and chatbot interface, reducing manual effort and increasing accessibility.

The paper uses single-cell transcriptomics and neural network classifiers to identify B cell signaling as critical for NK cell expansion in allogenic therapy.

This paper develops a 3D in vitro kidney model with immune cells to study inflammation and injury, showing monocyte migration and response to inflammatory stimuli.

The paper performs a meta-analysis of scRNA-seq data to identify disease-specific and shared chemokine-based cell communication patterns in immune diseases.

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

The paper introduces GENIX, a platform for identifying perturbation-relevant genes using gene association networks, applied to influenza vaccine responses in COVID-19 recovered patients.