Vessela Nedelcheva Kristensen

HiFIseek identifies gene-specific enrichment of high-impact mutations in genomic regions associated with cancer and breast cancer risk SNPs, showing limited agreement across CRR-score combinations.

PRANA adapts polygenic risk scores to non-European populations, improving predictive accuracy by 5%-20% in South Asian, East Asian, and Ashkenazi Jewish populations.

The paper uses case-control data from over 400,000 women to classify BRCA1 and BRCA2 variants, finding high consistency with ClinVar annotations for 785 previously unclassified variants.

This study identifies the loss of chromosome 13q14.2 as a key driver of breast cancer pathogenesis and drug response, showing its impact on tumor survival, cell cycle, and treatment susceptibility.

The paper uses multi-omics analysis to show macrophages in breast tumors correlate with better treatment response but worse survival, driven by immune suppression mechanisms.

The paper identifies cis-regulatory mutations in cancer that disrupt gene regulatory programs by affecting both transcriptional and post-transcriptional regulation.

The paper assesses breast cancer risks linked to rare missense variants in five susceptibility genes using logistic and mixture models, finding varying risk contributions across genes.

The paper develops a computational tool to predict drug combinations for TNBC by integrating transcriptional signatures with drug response data.

The paper analyzes rare copy number variants (CNVs) in breast cancer cases and controls, identifying associations with known and novel susceptibility loci.

The paper develops deep learning methods to infer spatial gene expression from pathology whole-slide images and links tumor heterogeneity to survival in breast and lung cancer.

The paper identifies haplotypes and LD patterns in 80 genes that differ between breast cancer patients and controls, and finds negative correlations in LD patterns for some genes.