David Ellinghaus

This study identifies 619 IBD risk signals, resolves 81 high-confidence variants, and prioritizes 664 candidate effector genes using GWAS, eQTL, and exome sequencing.

The paper uses statistical learning to decode T cell receptor associations with HLA alleles using a large dataset, identifying clonotypes linked to specific HLA alleles and infections.

This study identifies genetic risk factors associated with severe psoriasis and shows that polygenic risk scores can predict severe disease outcomes better than traditional risk factors.

The paper investigates how industrialization affects microbial and physiological traits in the human gut across diverse populations, finding homogenized microbiomes, reduced diversity, and impaired disease prediction accuracy in less industrialized groups.

This study performs a GWAS meta-analysis of psoriasis, identifying 109 susceptibility loci, including 45 new ones, and highlights potential therapeutic targets and disease mechanisms.

The paper traces the origin and spread of the IL23R variant rs11209026-A in Europe, linking its frequency changes to Neolithic agricultural practices and its protective role against inflammatory bowel diseases.

The paper identifies genetic variants associated with chronic sarcoidosis phenotypes using genome-wide association studies and functional analysis.

The paper introduces NeEDL, a network medicine-based method for detecting higher-order epistatic interactions in complex diseases, showing improved statistical significance and applicability across eight diseases.

GWAIS-Web provides a fast and secure web service for detecting genetic interactions in GWAS datasets using GPU and FPGA acceleration.

The paper develops PIA-M, a multimodal transformer-based tool for predicting HLA-II peptide presentation, achieving higher accuracy and faster runtime than existing methods.

EagleImp provides fast and accurate genome-wide phasing and imputation, outperforming existing tools in speed while maintaining or improving accuracy.

This study identifies a new susceptibility locus for severe COVID-19 through a detailed GWAS analysis in European populations, focusing on genetic variants associated with disease severity.

MAGScoT improves MAG quality and quantity while reducing computation time and resource use compared to existing bin-refinement tools.

EagleImp-Web provides a fast, secure web service for genotype phasing and imputation using FPGA acceleration and transparent algorithms.

This study examines how a major genetic risk factor for COVID-19 affects mortality and severity, finding stronger effects in younger adults.

This study performs a genome-wide association analysis of hemorrhoidal disease in 944,133 individuals, identifying 102 risk loci and linking them to vascular and tissue development pathways.

This study identifies shared and ethnicity-specific HLA associations with ulcerative colitis through trans-ethnic analysis of diverse populations.

This study identifies shared genetic loci between multiple system atrophy and inflammatory bowel disease using conjFDR, highlighting immune and gut-related molecular mechanisms.