Kristina Allgoewer

The paper re-mines serum proteomics data to identify post-translational modifications associated with Zika and dengue infections, highlighting specific modifications linked to each virus.

The paper identifies start-stop elements in 5' UTRs that repress translation by halting ribosomes, showing their prevalence in human genes and impact on cellular processes.

This study uses high-resolution proteomics to identify 26 differentially expressed proteins that can predict Zika virus infection with 72% accuracy using a machine learning model.

The paper quantifies gene expression regulation at multiple layers in response to ER stress in cervical cancer cells over time, identifying shared and stress-specific regulatory events.