Karsten Suhre

The paper validates the CvP-bias as a robust genomic marker for hyperthermostability across 1,963 microbial genomes, confirming its significance with high statistical confidence.

The paper finds that higher serum theobromine levels are associated with slower epigenetic ageing in humans, as measured by GrimAge and DNAmTL.

This study identifies 16 new genetic loci associated with plasma N-glycosylation in 10,000 individuals and links them to liver disease and inflammatory proteins.

The paper subtypes Type 2 Diabetes in a Middle Eastern cohort, identifies sex differences, and highlights the need for personalized treatment strategies based on subtype-specific risks.

LEOPARD completes missing views in multi-timepoint omics data by disentangling content and temporal representations, outperforming existing methods on benchmark datasets.

This study identifies genetic loci and candidate genes associated with date palm fruit size traits using GWAS and phenotypic data from diverse cultivars.

The paper develops an interpretable multimodal machine learning framework to predict distal sensorimotor polyneuropathy using clinical and molecular data, identifying key biomarkers and improving prediction accuracy with additional molecular modalities.

This study identifies genetic loci associated with fruit skin separation in date palm, showing both environmental and genetic contributions to the phenotype.

AutoFocus identifies multi-omic disease-associated modules across biological scales using a hierarchical framework, applied to type 2 diabetes and Alzheimer's datasets.

This study performs a genome-wide association study using mass spectrometry proteomics to identify pQTLs, finding that epitope effects may affect some affinity proteomics results while confirming others.

The paper identifies and replicates 4,248 associations with protein level ratios (rQTLs) using UK Biobank proteomics data, finding 2,527 novel rQTLs and revealing protein-protein interactions.

This study uses mass spectrometry proteomics to identify protein altering variants and map pQTLs, confirming target specificity and identifying novel variants not accessible by affinity proteomics.

This study presents the first large-scale IgA glycomics dataset from twins, identifies shared and specific genetic loci influencing IgA and IgG glycosylation, and shows genetic conservation across ethnicities.

The paper maps genetic associations with plasma proteins in 54,306 UK Biobank participants, identifying 10,248 new protein quantitative trait loci (pQTLs) and expanding the genetic architecture of the plasma proteome.

This study identifies genetic loci associated with dry date fruit color using genome sequences and image data from 199 samples.

This study uses scRNA-seq to analyze kidney allograft biopsies and identifies recipient-derived fibroblasts and other cell states associated with fibrosis and rejection.

The Qatar Genome Program sequenced 6,045 individuals, identifying 88 million variants, including novel ones, and revealed genetic structure and disease-related markers in the Qatari population.

The paper develops epigenetic scores (EpiScores) for plasma proteins to predict disease risk, finding 137 associations with incident morbidities independent of known factors.

The paper uses systems biology analysis of whole-genome sequences from 298 SB case-control pairs to identify key pathways and genes associated with spina bifida risk.

SGI identifies clinical subgroups in omics datasets using hierarchical clustering and association testing, demonstrated on a metabolomics dataset from a type 2 diabetes study.

This study trains a variational autoencoder on metabolomics data to learn nonlinear latent representations and validates its generalizability across different disease cohorts.

This paper introduces a cutoff selection algorithm for correlation networks that uses prior knowledge to improve network reconstruction, showing better performance than statistical cutoffs across multiple datasets.

The paper measures 12-year changes in blood-circulating proteins in patients with and without gastric bypass surgery, finding long-term associations with BMI and lipid levels.

This study uses deep serum proteomics to identify 20 protein biomarkers for predicting type 2 diabetes and finds 48 proteins with causal roles in its development.

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

This study identifies twelve genetic loci associated with human blood plasma N-glycome composition through genome-wide association analysis, revealing both direct and indirect genetic influences on glycosylation.

The paper identifies four conserved genes in male date palms, supporting a two-mutation model for the evolution of dioecy from hermaphroditism.

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.

ProGeM prioritizes candidate causal genes at molecular QTLs by integrating biological and genome annotations, achieving high accuracy in identifying true positives.

MoDentify identifies regulated metabolomics modules driven by phenotypes across different resolution levels, offering higher statistical power than classical methods.