I have an irregularly shaped protein complex, with extrememly different particle sizes (it's long and shaped like an L). This is problematic for particle picking because some views are relatively globular and look like circles, but others are long and extended.
I have two problems.
First, is there a way to optimize the picking? The picking module mseems to be looking for gaussian blobs, but there don't seem to be any options that account for differences in size or shape. For example, DogPicker.py allows you to look for size ranges. Could I pick from the same dataset using multiple parameters and join the picks later?
Second, because the picking is non-ideal, my particles are often not centered correctly. Is there a way to recenter the particles? When you make a new Refinement Package after 2D classification do the particles get recentered based on the center of mass of the 2D class?