Abstract text (incl. figure legends and references)
Cryo-electron tomography (Cryo-ET) has become an essential tool for in situ structural biology. Recent developments both in hardware and software lead to (relatively) high throughput in tilt-series acquisition as well as more automated tilt-series alignment and tomogram reconstruction. For subsequent tomogram analysis, most of the method development has been focused on automated particle picking and subtomogram averaging (STA). While these techniques are essential for high-resolution structure determination, they are often "blind" to the rich cellular environment from which the particles come and leave a large portion of the tomograms unexplored. In my talk I will discuss advantages and ways of incorporating contextual information into the particle picking and STA workflows and show how using meta data from STA can be used to analyze the remaining parts of cellular tomograms.