David H. Meyer
The FOR5504 generates large amounts of OMICS data, such as RNA-seq, ChIP-seq, CUT&Tag, ATAC-seq, CUT&Break, END-seq, MS-measurements quantifying peptides, untargeted and targeted metabolomics.
The central project on data integration facilitates the planning, analysis, and integration of these OMICs experiments within and across the sub-projects. It also oversees data management to ensure efficient utilization and reproducibility among the scientists. The complexity of these datasets necessitates advanced analytical approaches, such as biologically informed deep-neural networks, non-negative matrix factorization, and multi-OMICs correlation analysis.
Additionally, this central project offers comprehensive training to members of the research unit, empowering researchers to effectively analyze their own data and ensure meticulous documentation of their work, in alignment with FAIR data principles.
PROJECT RELATED PUBLICATIONS
- Hansel-Hertsch, R. et al. Landscape of G-quadruplex DNA structural regions in breast cancer. Nat Genet 52, 878-883 (2020).
- Hansel-Hertsch, R. et al. G-quadruplex structures mark human regulatory chromatin. Nat Genet 48, 1267-1272 (2016).
- Mueller, M. M. et al. DAF-16/FOXO and EGL-27/GATA promote developmental growth in response to persistent somatic DNA damage. Nat Cell Biol 16, 1168-1179 (2014).
- Wang, S., Meyer, D. H. & Schumacher, B. H3K4me2 regulates the recovery of protein biosynthesis and homeostasis following DNA damage. Nat Struct Mol Biol 27, 1165-1177 (2020).
- Lensing, S. V. et al. DSBCapture: in situ capture and sequencing of DNA breaks. Nat Methods 13 (2016).
- Edifizi, D. et al. Multilayered Reprogramming in Response to Persistent DNA Damage in C. elegans. Cell Rep 20, 2026-2043 (2017).
- Meyer, D. H. & Schumacher, B. BiT age: A transcriptome-based aging clock near the theoretical limit of accuracy. Aging Cell 20, e13320 (2021).
