Jaap Heringa

This study introduces tumor break load (TBL) as a measure of genomic instability across cancers, showing its association with gene expression changes and clinical outcomes.

The paper introduces an ensemble of deep learning models (PIPENNs) for predicting protein interface residues, showing improved performance over existing methods across different interaction types.

The paper introduces SeRenDIP-CE, a sequence-based method for predicting conformational epitopes, achieving better performance than existing predictors on an antibody-antigen structure.

The paper compares genetic interaction patterns between gene-specific transcription factors and signaling genes in yeast, finding inversion is more common in transcription factors due to differential regulation.

This study constructs and validates a Petri net model of Wnt/β-catenin signaling to investigate its behavior under physiological and pathophysiological conditions, revealing dose- and time-dependent responses and higher pathway activity in hyperactive signaling.