Nikolina Nakić

VIDRA models genetic dose-response relationships to predict drug mechanisms, therapeutic potential, and adverse events using phenotypically associated variants.

The paper identifies USP18 as a negative regulator of interferon response at a lupus risk locus through trans-eQTL analysis in lymphoblastoid cell lines.

The paper integrates genetic and epigenetic data to identify autoimmune-specific enhancer dysregulation in CD4+ T cells and its role in disease pathogenesis.

The paper maps eQTLs during T cell activation and identifies immune disease risk variants that regulate gene expression dynamics, showing colocalization with disease-associated genes.

This study uses genetic associations from GWAS and network propagation to identify drug targets enriched for clinical success.

The paper identifies T cell states associated with immune disease variants by analyzing chromatin activity across different activation states.

This study identifies direct Hes1 target genes in pancreatic progenitor cells, revealing Notch signaling's role in repressing tip cell fate through repression of key regulators like Ptf1a and Gata4.

The paper identifies HES1 target genes using ChIP-seq and RNA-seq in hESC lines, revealing HES1's role in pancreatic development through Notch pathway regulation and suppression of intestinal gene programs.

This study identifies β cell-specific lncRNAs that regulate transcriptional networks and show dysregulation in type 2 diabetes.