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Deep Generative Modeling for Volume Reconstruction in Cryo-Electron Microscopy. (arXiv:2201.02867v2 [eess.IV] UPDATED)
cs.LG updates on arXiv.org arxiv.org
Recent breakthroughs in high resolution imaging of biomolecules in solution
with cryo-electron microscopy (cryo-EM) have unlocked new doors for the
reconstruction of molecular volumes, thereby promising further advances in
biology, chemistry, and pharmacological research amongst others. Despite
significant headway, the immense challenges in cryo-EM data analysis remain
legion and intricately inter-disciplinary in nature, requiring insights from
physicists, structural biologists, computer scientists, statisticians, and
applied mathematicians. Meanwhile, recent next-generation volume reconstruction
algorithms that combine generative modeling with end-to-end unsupervised deep
learning …