Zeyneb Kurt

This study evaluates generative AI models for improving cell-type classification in scRNA-seq data by generating synthetic cells and comparing model performance.

This study identifies a circRNA-miRNA-mRNA network in breast cancer, highlighting potential biomarkers for basal-like breast cancer classification.

This study identifies shared and distinct genetic pathways between human and mouse in coronary artery disease using multi-omics data and GWAS, showing over 75% shared pathways.

The paper identifies a gene co-expression module, the pink module, associated with PAH severity, genetic risk, vascular cell types, and therapeutic targets through multiomics integration.

DepEst provides 11 dependency score estimators for gene network inference algorithms, available as an R package with parallel and serial execution capabilities.

Mergeomics integrates diverse genomics resources to identify pathogenic perturbations by analyzing disease-associated pathways and gene networks, revealing novel cholesterol regulators.