Building Proteins in a Day: Efficient 3D Molecular Reconstruction
This addresses the challenge of efficient 3D structure estimation for molecules like proteins and viruses in biology and medicine, representing a strong specific gain rather than a broad paradigm shift.
The paper tackles the problem of 3D molecular reconstruction from 2D Cryo-EM images by introducing a framework with stochastic optimization and a novel technique that reduces objective function evaluation cost by over five orders of magnitude, resulting in an approach that can estimate structures in about a day on a single workstation.
Discovering the 3D atomic structure of molecules such as proteins and viruses is a fundamental research problem in biology and medicine. Electron Cryomicroscopy (Cryo-EM) is a promising vision-based technique for structure estimation which attempts to reconstruct 3D structures from 2D images. This paper addresses the challenging problem of 3D reconstruction from 2D Cryo-EM images. A new framework for estimation is introduced which relies on modern stochastic optimization techniques to scale to large datasets. We also introduce a novel technique which reduces the cost of evaluating the objective function during optimization by over five orders or magnitude. The net result is an approach capable of estimating 3D molecular structure from large scale datasets in about a day on a single workstation.