ADVANCED ALGORITHM DEVELOPMENT FOR CRYO EM CALCULATIONS

该项目的目标是填补低温电子研究发展之间差距， 这是一个非常重要的任务，它将利用冷冻电镜（cryo-EM）和大规模科学计算的最新进展，从而更好地在常规和及时的基础上实现高分辨率单粒子重建。为了实现这一目标，我们将在新的数值算法的设计和实施方面进行研究，这将导致执行高分辨率单粒子重建所需的工作量显着减少。我们的工作将包括通过开发一种并行算法来提高粒子方向搜索的效率，该并行算法执行渐进的局部投影匹配，开发用于增强 3-D重建的收敛性和鲁棒性，寻求替代的局部优化算法以同时校正粒子取向参数和3-D结构，并将局部优化方案与将在项目E中开发的全局组合搜索策略相结合。除了设计和实现新的算法，我们还将开发高度并行计算的策略，以加快单粒子重建中的计算密集型任务。这些将包括最佳的数据分解，任务调度，以及利用内存层次结构和减少I/O延迟的技术。 在这项研究的所有领域，我们将与本方案其他项目的研究人员密切互动和合作，主要目标是确保我们的工作成果纳入天基信息平台（项目A），SPARX（项目B），为单个粒子图像的自动装箱而开发的软件技术（项目D），以及为颗粒间排列参数的全局优化而开发的软件技术（项目E）。

The goal of this project is to fill in the gap between research developments in cryo-electron microscopy (cryo-EM) and recent advances in large-scale scientific computing, and thus to better enable high-resolution single particle reconstructions on a routine and timely basis. To accomplish this goal, we will conduct research in the design and implementation of new numerical algorithms that will lead to significant reduction in the amount of work required to perform high-resolution single particle reconstructions. Our work will include improving the efficiency of particle orientation search by developing a parallel algorithm that performs progressively localized projection matching, developing techniques for enhancing the convergence and robustness of 3-D reconstruction, seeking alternative local optimization algorithms to simultaneously correct both the particle orientation parameters and the 3-D structure, and combining the local optimization scheme with a global combinatorial search strategy to be developed in Project E. In addition to designing and implementing new algorithms, we will also develop strategies for highly parallel computation to speed up the compute-intensive tasks in single particle reconstructions. These will include optimal data decomposition, task scheduling, and techniques for exploiting memory hierarchy and reducing I/O latency. In all of the areas of this research, we will interact and collaborate closely with investigators from the other projects in this Program, the primary goal being to ensure that the results of our work are integrated into SPIDER (Project A), SPARX (Project B), software technology that is developed for automated boxing of images of single particles (Project D), and software technology that is developed for global optimization of inter-particle alignment parameters (Project E).