The Nobel Prize in Chemistry 2017 rewarded the development of cryo-electron microscopy for the high-resolution structure determination of biomolecules in solution.
Since its opening in 2018, the Stanford-SLAC Cryo-EM Facility has installed four cutting-edge microscopes operating in projective and tilt-series acquisition mode, for single-particle analysis (SPA) and tomography (cryoET) projects respectively.
Altogether, SLAC has already generated petabytes of cryoEM data, the processing of which required dozens of petaFLOPS in performance, resulting in a swarm of structural insights in our understanding of biological mechanisms, from the molecular to the cellular level.
Looking forward, the new challenges and opportunities of both projective and tomographic imaging techniques offered by cryoEM will need and benefit from ML application development. We illustrate below some of the scientific areas where ML would help, the biological problem space. We also provide a tentative list of the potential areas where we will push development, the technical problem space.