Beata Turoňová: Image Processing
We aim to facilitate in situ structural analysis by developing novel algorithms for cryo electron tomography and subtomogram averaging. Our software method development focuses on improving tomogram quality and integrating contextual information into subtomogram averaging routines. To ensure their robustness, the methods are tested on a variety of samples from virus-like particles (e.g. HIV, Sars-Cov-2) and real viruses (e.g. Sars-Cov-2, vaccinia) to very large macromolecular complexes (e.g. nuclear pore complexes). Our main goal is to allow for reliable and objective analysis of tomograms as well as macromolecular complexes.
Contextual subtomogram averaging
Most of the current effort to push the achievable resolution in cryo electron tomography focuses on methodological improvements on the level of subtomogram averaging. Valuable contextual information provided either directly within the tomogram or by other sources (molecular dynamics, mass spectrometry) is thereby often neglected. In our group, we explore the possibility to incorporate such information into various steps along the data processing workflow, thereby facilitating not only subtomogram averaging but also structural analysis on the whole tomogram level.
Quality assessment and improvement
In cryo electron tomography, the definition of data quality is ill-defined and can often only be evaluated based on the final outcome (e.g. attainable resolution of subtomogram averaging). We work on establishing an objective way to assess the performance of various intermediate steps within the typical processing workflow. Our ultimate goal is to obtain the best possible result by improving the quality of intermediate outcomes rather than increasing the total amount of data.
Currently we have open positions for Master student, PhD student, and postdoctoral researcher. If you are interested please send your CV and a brief motivation letter describing your background and particular research interests to Beata.Turonova@biophys.mpg.de.