Nicola Mulder

The paper analyzes epigenetic gene variants in African and European populations to find frequency differences, trait associations, and functional impacts.

This study examines how Microsporidia MB infection affects gene expression and gut microbiota in Anopheles arabiensis mosquitoes at different times post blood meal.

JasMAP improves GWAS power in multi-way admixed populations by jointly analyzing genotype and ancestry associations, identifying 13 significant SNPs in a South African Coloured population with TB.

This study simulates genomic data from diverse populations to assess GWAS tool performance and proposes an optimized framework for analyzing GWAS data in non-European populations.

This study evaluates HLA imputation accuracy in a West African population using different tools and reference panels, finding HIBAG and the H3Africa panel to be most effective.

This study identifies novel genetic variants associated with cardiovascular traits in African and European populations using the UK Biobank, highlighting population-specific genetic architecture.

This study identifies 817 genetic variants in Europeans and 3 in Africans associated with pulmonary function traits, highlighting distinct genetic architecture between populations.

The paper examines how genetic risk factors and gene expression influence longitudinal changes in brain connectivity and dementia progression in Alzheimer's disease.

The paper identifies cancer-associated mutations in MAPK pathway genes across 40,848 tumors and links them to poor outcomes and drug responses.

This paper introduces BiGen, a structural equation model that integrates genetic, neuroimaging, and clinical data to analyze complex brain diseases like Alzheimer's and glioblastoma.

The paper conducts a GWAS to analyze changes in brain connectivity over disease progression in Alzheimer's, identifying genetic associations with structural connectivity changes.

GenGraph generates genome graphs using multiple sequence alignments and provides tools for manipulation in Python, enabling flexible genomic analysis.

ANIMA integrates clinical phenotype and microarray data to reconstruct disease endophenotypes across multiple organizational scales.