Oleg Borisov

This study identifies mQTLs for serum and urine metabolites across ancestries, revealing ancestry-specific genetic effects and linking them to disease traits.

This study identifies 36 genetic loci associated with recurrent UTIs and highlights PSCA as a key gene involved in urinary epithelial defense against bacteria.

The paper develops a transcriptome-based method to match bulk RNA-seq data from kidney cell lines to single-cell reference datasets, identifying accurate cell type identities and evaluating method performance.

This study performs GWAS on the human urine proteome, identifying genetic associations with 20 proteins and linking them to disease risk and gene expression.

This study identifies SLC25A48 as a human mitochondrial choline transporter and shows that loss-of-function mutations lead to elevated choline levels in urine and plasma.

The paper identifies gene-metabolite associations using exome sequencing and metabolomics, revealing graded effects of rare variants on traits and diseases.

The paper applies statistical learning methods to develop sparser polygenic models for LDL-cholesterol prediction using UK Biobank data, showing competitive performance compared to classical approaches.

The paper introduces an AI-driven method that uses facial images to prioritize exome data, achieving 99% top-10 accuracy in identifying disease-causing genes.