Martijn A. Huynen

The paper uses imaging-guided single-cell multiomics to identify shared autoreactive CD4+ T-cell responses in blood, lymph nodes, and tissues of patients with systemic autoimmune diseases.

KG-Bench benchmarks graph neural networks for drug repurposing using the Open Targets dataset, finding TransformerConv achieves the highest performance.

The paper identifies a conserved gene co-expression module in Drosophila linked to epilepsy, showing metabolic rate and AMPK activity influence seizure susceptibility.

The paper establishes an in vitro model to generate inflammatory fibroblasts and shows they produce ECM with properties similar to tissue-remodelling fibroblasts, enhancing immune suppression.

The paper presents a chromosome-scale genome assembly of Alvinella pompejana and analyzes its gene content to understand adaptations to extreme environments.

CompaCt integrates complexome profiling data across species to identify conserved and species-specific protein complexes and interactions, improving characterization through comparative analysis.

This paper identifies c17orf80 as a mitochondrial membrane protein interacting with nucleoids but not essential for mtDNA maintenance or expression in human cells.

The paper identifies and validates a comprehensive list of mitochondrial proteins in Plasmodium falciparum using Bayesian statistics and experimental confirmation.

The paper investigates family-specific contributions to de novo mutations and finds that stochasticity explains most of the variation.

CEDAR provides a database for complexome profiling data with standardized formats, a web interface, and tools for analysis and exploration.

The paper identifies 285 candidate ciliary genes using integrated genomic, proteomic, and transcriptomic data, validated by experimental evidence and creating a resource for ciliopathy research.

COPAL aligns complexome profiles to identify changes in mitochondrial protein complex abundance caused by Barth syndrome mutations.

The paper predicts high-resolution metabolomes from metagenomic datasets, showing body-site specific metabolomes and identifying common cosmetics ingredients as major factors shaping the human skin microbiome.