István A. Kovács

The paper reports a C. elegans extracellular interactome dataset, revealing new interactions between signaling pathways and potential roles in human disease mechanisms.

This study shows bacterial motility patterns smoothly transition between run-and-tumble and hop-and-trap behaviors across varying spatial confinement and disorder.

The paper introduces a positive statistical benchmark to assess network agreement, showing that observed overlaps are often close to the best-case scenario despite limited shared interactions.

The paper evaluates 24 network-based methods for predicting protein-protein interactions across five interactomes, identifies top-performing methods, and validates their predictions experimentally.

The paper constructs a high-quality yeast binary interactome map and compares inner- and outer-complexome organization, finding the outer-complexome contains more interactions and exhibits higher functional heterogeneity.

The paper presents HuRI, a comprehensive human protein-protein interaction map, and demonstrates its utility in understanding cellular function and disease mechanisms.

The paper challenges the Triadic Closure Principle in protein interaction prediction and introduces the L3 principle, which outperforms existing methods and identifies novel interactions.