Hajk-Georg Drost
Computational Biology and Causal Inference
Max Planck Institute for Biology Tübingen
Adjunct faculty in: IMPRS
Vita
- PhD studies, Martin Luther University Halle, 2013-2015
- Postdoctoral Researcher, University of Cambridge, 2015-2018
- Senior Postdoctoral Researcher, University of Cambridge, 2018-2019
- Research Group Leader, Department of Molecular Biology, MPI for Biology, since 2019
Research Interest
Intelligent software is adaptive, scalable, and user-friendly. Inspired by recent advancements in deep learning and cloud-computing, we develop intelligent open-source software and harness it to translate the predictive capacity of machine learning into molecular biology research. Our ultimate aim is to predict the regulatory evolution of gene expression and causally associate molecular mechanisms of gene regulation with phenotypic changes in complex traits. We approach this by integrating comparative and functional genomics at tree-of-life scale with evolutionary transcriptomics and causal inference of gene regulatory networks to derive a data-driven predictive framework of trait evolvability.
Our Software:
Available PhD Projects
- Currently not recruiting PhD students
Selected Reading
- B Buchfink, K Reuter, HG Drost*. Sensitive protein alignments at tree-of-life scale using DIAMOND. Nature Methods, 18, 366–368 (2021).
- M Quint, HG Drost et al. A transcriptomic hourglass in plant embryogenesis. Nature 490 (7418), 89-101 (2012). (journal cover).
- HG Drost* et al. myTAI: evolutionary transcriptomics with R. Bioinformatics 34 (9), 1589-1590 (2018).
- HG Drost* et al. Post-embryonic hourglass patterns mark ontogenetic transitions in plant development. Molecular Biology and Evolution 33 (5), 1158- 1163 (2016). (journal cover).
- 2015 – HG Drost et al. Evidence for Active Maintenance of Phylotranscriptomic Hourglass Patterns in Animal and Plant Embryogenesis. Molecular Biology and Evolution 32 (5), 1221-1231 (2015).