Fast 3D Reconstruction Algorithms for Cryo-EM

描述（申请人提供）：本研究拟开发用于低温电子显微镜（Cryo-EM）小颗粒高分辨率三维重建的快速期望最大化（EM）算法。该算法结合了显微镜的对比度传递函数（CTF），可用于任意基函数。此外，提出了两种策略，将算法的速度提高了1000倍。这两种策略是：(1)域缩减，加快算法的E步，以及(2)在商用显卡上实现，其中图形处理器的大规模并行性加快了整个算法。基于核糖体和IP3R Ca+通道蛋白结构的初步模拟结果表明，该算法的E步和M步快速准确。

DESCRIPTION (provided by applicant): This research proposes to develop fast expectation-maximization (EM) algorithms for 3D reconstruction of high resolution reconstruction of small particles in Cryogenic Electron Microscopy (Cryo-EM). The proposed algorithm incorporates the contrast transfer function (CTF) of the microscope and can be used with any basis functions. Further, two strategies are proposed to speed up the algorithm by a factor of 1000. The two strategies are (1) domain reduction where the E step of the algorithm is sped up, and (2) implementation on commodity graphics cards, where the massive parallelism of the graphics processors speeds up the entire algorithm. Preliminary results using simulations based on ribosome and the IP3R Ca+ channel protein structure show that the E and M steps of the proposed algorithm are fast and accurate. The proposed research extends previous work by (1) further developing the domain reduction strategy into a multi-resolution strategy, (2) systematically parallelizing the M step, and (3) implementing and validating the complete algorithm. Further, systematic software design is planned for implementing the algorithm on graphics processor units. This software will be made available on the world-wide web for other researchers. The algorithm will be validated using simulations and real-world Cryo-EM images. The reconstruction accuracy will be measured by the average mean squared error in reconstruction, and the resolution will be measured by Fourier shell correlation. The accuracy will also be compared to the reconstruction accuracy of conventional algorithms. The speed of the algorithm will be measured as a function of number of images and signal to noise ratio.