Gerard A. Bouland

The paper uses long-read sequencing to uncover structural complexity in Alzheimer's disease GWAS loci, showing that lead SNPs often miss key regulatory variants.

This study identifies Apbb1ip as a genetic modulator of immune gene co-expression in aged mouse hippocampus, revealing age-related transcriptomic changes and immune response upregulation.

The paper identifies genetic variants associated with protein abundance and altered protein-protein correlations in the Gyrus Temporalis Medius in Alzheimer's Disease patients.

This paper introduces scAGG, a model for classifying Alzheimer's disease from single-nucleus RNA-seq data by aggregating single-cell embeddings, and finds it accurately classifies AD and healthy controls with disease severity ordering in the latent space.

The paper introduces gsQTL, a method that links genetic risk variants to gene sets by analyzing shared variability, showing improved performance over traditional approaches.

The paper uses scRNA-seq data to identify gene expression rewiring in Alzheimer's Disease linked to risk variants by analyzing differential correlations across cell types.

This paper identifies age and Alzheimer's disease-associated somatic mutations in excitatory neurons using WGS and scRNA-seq data from the ROSMAP project.

The paper shows that binarized gene expression in scRNA-seq is as informative as count-based expression and scales better to larger datasets.

The paper introduces differential dropout analysis to detect biological variation in single-cell RNA sequencing data and shows it outperforms count-based methods.

The paper introduces the R-package CONQUER to analyze type 2 diabetes risk loci by integrating genomic and epigenomic data, revealing tissue-shared effects on metabolic and HLA pathways.