Fast 3D Reconstruction Algorithms for Cryo-EM

用于冷冻电镜的快速 3D 重建算法

• 批准号: 8318254
• 负责人: Hemant D Tagare
• 金额: $ 38.93万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-15 至 2014-07-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8318254
• 关键词: Accounting; Affect; Algorithms; Architecture; Color; Computational algorithm; Computer Graphics; Computer software; Data; Development; Drug Formulations; Electron Microscopy; Equation; Evaluation; Funding; Goals; Grant; Graph; ITPR1 gene; Image; Inositol; Internet; Libraries; Measures; Methods; Microscope; Noise; Outcomes Research; Pharmaceutical Preparations; Process; Process Measure; Programming Languages; Property; Proteins; Publications; Research; Research Personnel; Resolution; Ribosomes; Shapes; Signal Transduction; Simulate; Software Design; Solutions; Speed; Structure; Suggestion; Techniques; Testing; Therapeutic Intervention; Time; United States National Library of Medicine; Variant; Work; base; cryogenics; expectation; flexibility; parallel computing; particle; programs; protein structure; receptor; reconstruction; research study; simulation; theories; three dimensional structure; trend; tripolyphosphate; Accounting; Affect; Algorithms; Architecture; Color; Computational algorithm; Computer Graphics; Computer software; Data; Development; Drug Formulations; Electron Microscopy; Equation; Evaluation; Funding; Goals; Grant; Graph; ITPR1 gene; Image; Inositol; Internet; Libraries; Measures; Methods; Microscope; Noise; Outcomes Research; Pharmaceutical Preparations; Process; Process Measure; Programming Languages; Property; Proteins; Publications; Research; Research Personnel; Resolution; Ribosomes; Shapes; Signal Transduction; Simulate; Software Design; Solutions; Speed; Structure; Suggestion; Techniques; Testing; Therapeutic Intervention; Time; United States National Library of Medicine; Variant; Work; base; cryogenics; expectation; flexibility; parallel computing; particle; programs; protein structure; receptor; reconstruction; research study; simulation; theories; three dimensional structure; trend; tripolyphosphate

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.

描述（由申请人提供）：本研究提议开发快速期望最大化（EM）算法，用于3D重建小颗粒在低温电子显微镜（Cryo-EM）中的高分辨率重建。所提出的算法包含显微镜的对比传递函数（CTF），可与任何基础函数一起使用。此外，提出了两种策略，以加快算法的速度1000倍。两种策略是（1）域减少，其中算法的E步骤被加速，并且（2）在商品图形卡上实现，其中图形处理器的庞大并行性加快了整个算法的速度。使用基于核糖体和IP3R CA+通道蛋白结构的模拟的初步结果表明，所提出的算法的E和M步骤快速准确。 拟议的研究通过（1）进一步将减少域策略发展为多分辨率策略，（2）系统地将M步行平行，以及（3）实施和验证完整算法。此外，计划在图形处理器单元上实现算法的系统软件设计。该软件将在全球网络上为其他研究人员提供。该算法将使用模拟和现实世界冷冻EM图像进行验证。重建精度将通过重建中的平均平方误差来衡量，分辨率将通过傅立叶壳相关来衡量。该精度还将与常规算法的重建精度进行比较。该算法的速度将作为图像数量和信号与噪声比的函数进行测量。