Johannes Raffler

The HuMet Repository provides time-resolved metabolomics data from six metabolic challenges in healthy males, enabling analysis of dynamic metabolic responses and pathway interactions.

The paper integrates genomic and proteomic data to identify genetic variants influencing host proteins interacting with SARS-CoV-2, revealing potential drug targets and disease mechanisms.

This study identifies genetic associations with metabolite levels across multiple cohorts and links these variants to clinical outcomes like type 2 diabetes and macular telangiectasia type 2.

This study identifies 11 genetic loci associated with salivary metabolites in 1,419 individuals, revealing novel saliva-specific associations and potential clinical applications.

The paper evaluates missing data handling strategies in untargeted metabolomics data, finding that KNN imputation with variable pre-selection is robust across multiple evaluation schemes.

The paper performs a GWAS on blood plasma proteome data from two cohorts to identify SNP-protein associations linked to various diseases and creates a genome-proteome network and web tool for analysis.