Project Group Leader, Structural Biochemistry
Computational Structural Biology
The Computational Structural Biology group explores new software-based methods to stretch the boundaries of what image processing and machine learning can currently do for structural biology.
Methodologically, the focus is on object localization and segmentation of cryo-electron microscopy data sets. In addition, the group is working on the automation of existing workflows and pipelines. The group supports other scientists in the department with projects involving image- and data-analysis.
These methods enable scientists to gain insights from experiments that cannot be obtained by manual analysis, or only with a great deal of time.
Schöenfeld F, Stabrin M, Shaikh TR, Wagner T, Raunser S (2022). Accelerated 2D Classification With ISAC Using GPUs. Front Mol Biosci.
Wang Z, Grange M, Pospich S, Wagner T, Kho A.L, Gautel M, Raunser S (2022). Structures from intact myofibrils reveal mechanism of thin filament regulation through nebulin. Science
Wagner T, Raunser S (2020). The evolution of SPHIRE-crYOLO particle picking and its application in automated cryo-EM processing workflows. Communications Biology
Stabrin M, Schoenfeld F, Wagner T, Pospich S, Gatsogiannis C, Raunser S (2020). TranSPHIRE: automated and feedback-optimized on-the-fly processing for cryo-EM Nat Commun
Wagner T, Lusnig L, Pospich S, Stabrin M, Schönfeld F, Raunser S (2020).Two particle-picking procedures for filamentous proteins: SPHIRE-crYOLO filament mode and SPHIRE-STRIPER. Acta Cryst Sect D Struct Biol.
Wagner T, Merino F, Stabrin S, Moriya T, Antoni C, Apelbau A, Hagel P, Sitsel O, Raisch T, Prumbaum D, Quentin D, Roderer D, Tacke S, Siebolds B, Schubert E, Shaikh TR, Lill P, Gatsogiannis C, Raunser S (2019). SPHIRE-crYOLO is a fast and accurate fullyautomated particle picker for cryo-EM. Communications Biology