TiltRec: an ultra-fast and open-source toolkit for cryo-electron tomographic reconstruction.

Yanxin Jiao, Hongjia Li, Yang Xue, Guoliang Yang, Lei Qi, Fa Zhang, Dawei Zang, Renmin Han
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Abstract

Motivation: Cryo-electron tomography (cryo-ET) has revolutionized our ability to observe structures from the subcellular to the atomic level in their native states. Achieving high-resolution reconstruction involves collecting tilt series at different angles and subsequently backprojecting them into 3D space or iteratively reconstructing them to build a 3D volume of the specimen. However, the intricate computational demands of tomographic reconstruction pose significant challenges, requiring extensive calculation times that hinder efficiency, especially with large and complex datasets.

Results: We present TiltRec, an open-source toolkit that leverages the parallel capabilities of Central Processing Units and Graphics Processing Units to enhance tomographic reconstruction. TiltRec implements six classical tomographic reconstruction algorithms, utilizing optimized parallel computation strategies and advanced memory management techniques. Performance evaluations across multiple datasets of varying sizes demonstrate that TiltRec significantly improves efficiency, reducing computational times while maintaining reconstruction resolution.

Summary: TiltRec effectively addresses the computational challenges associated with cryo-ET reconstruction by fully exploiting parallel acceleration. As an open-source tool, TiltRec not only facilitates extensive applications by the research community but also supports further algorithm modifications and extensions, enabling the continued development of novel algorithms.

Availability and implementation: The source code, documentation, and sample data can be downloaded at https://github.com/icthrm/TiltRec.

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TiltRec:一个用于低温电子层析重建的超快速开源工具包。
背景:低温电子断层扫描(cryo-ET)已经彻底改变了我们观察从亚细胞到原子水平结构的能力。实现高分辨率的重建包括收集不同角度的倾斜序列,然后将它们反向投影到三维(3D)空间或迭代重建它们以构建标本的三维体积。然而,层析重建复杂的计算需求带来了巨大的挑战,需要大量的计算时间,这阻碍了效率,特别是对于大型和复杂的数据集。结果:我们提出了TiltRec,一个开源工具包,利用cpu和gpu的并行能力来增强层析重建。TiltRec实现了六种经典的层析重建算法,利用优化的并行计算策略和先进的内存管理技术。跨多个不同大小数据集的性能评估表明,TiltRec显著提高了效率,在保持重建分辨率的同时减少了计算时间。结论:TiltRec通过充分利用并行加速,有效地解决了与冷冻et重建相关的计算挑战。作为一个开源工具,TiltRec不仅促进了研究界的广泛应用,而且还支持进一步的算法修改和扩展,使新算法的持续发展成为可能。可用性和实现:源代码、文档和样本数据可在https://github.com/icthrm/TiltRec.Supplementary上下载;补充数据可在Bioinformatics在线获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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