Marc Zapatka

This study uses pan-cancer phosphoproteomics to identify therapeutic targets and improve precision oncology by analyzing 1,998 tumor samples and developing new scores for kinase activity and immune response.

The paper benchmarks DNA methylation sequencing workflows against an experimental gold-standard, identifying superior workflows and developing a sustainable benchmarking platform.

This study compares the reprogramming dynamics of pluripotent and trophoblast stem cell states using multi-omics analysis, revealing distinct trajectories and reprogramming markers.

This paper introduces a method to generate localized DNA double-strand breaks in cell populations using UV-irradiation with photomasks, enabling the study of genome rearrangements and DNA damage response.

This study identifies MDM4 as a critical target of 1q gain in TP53wt Burkitt lymphoma, showing its role in evading cell cycle arrest and highlighting its therapeutic potential.

confFuse identifies high-confidence fusion genes from RNA-seq data by scoring candidates based on structural motifs, reducing false positives while maintaining high accuracy.