Dragana Vuckovic

LongOmicsTraj provides a topology-based framework to represent and query longitudinal omics trajectories, identifying corticosteroid response genes with temporal patterns across treatment groups.

The paper combines natural and engineered genetic variation to identify 22 non-coding variants affecting haematological traits and shows how a CUX1 variant impacts megakaryopoiesis.

The paper identifies PIK3R3 as a candidate regulator of platelet count in Bangladeshi ancestry individuals through GWAS and functional analysis.

This study identifies 557 new gene-trait associations for hematological traits using transcriptome-wide association analysis in UK Biobank data.

This study identifies 5,552 blood-cell trait-variant associations across 746,667 individuals from 5 global populations, including 71 novel loci and ancestry-specific variants not found in European ancestry populations.

This study identifies 5,106 new genetic variants associated with blood cell traits using large-scale GWAS, highlighting the polygenic and monogenic basis of hematopoiesis.

This study compares machine learning and univariate methods for constructing polygenic scores for 26 blood cell traits using UK Biobank and INTERVAL data, showing improved performance with learning methods.

This study performs GWAS on blood cell flow-cytometry phenotypes, identifies variant-trait associations, and links them to cellular structures and disease mechanisms.

This study identifies 6 new blood pressure loci and 48 genes involved in BP regulation using GWAS and gene expression data from blood and kidney tissues.

MultiMeta performs meta-analysis of multi-phenotype GWAS by combining results from different cohorts using an inverse-variance based method in an n-dimensional setting.