使用潮来快速和内存高效地搜索大规模质谱数据
Attila Kertesz-Farkas1, Frank Lawrence Nii Adoquaye Acquaye1, Vladislav Ostapenko1
1Department of Data Analysis and Artificial Intelligence and Laboratory on AI for Computational Biology, Faculty of Computer Science, HSE University, Moscow 109028, Russia.
Journal of proteome research
|August 12, 2025
概括
新潮软件显著加快了对庞大的双重质谱数据集的分析速度,在标准硬件上高效处理超过1000万个光谱和70亿个. 这种开源工具提供更快的性能与更低的内存需求.
科学领域:
- 蛋白质组学是指蛋白质组学.
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
背景情况:
- 协奏质谱 (MS/MS) 数据分析软件在过去30年里取得了很大的进步.
- 现有的工具面临极大数据集 (数百万的光谱或数十亿的) 的局限性.
研究的目的:
- 增强Tide搜索引擎,用于分析大规模的MS/MS数据集.
- 提高大规模蛋白质组数据处理的速度和内存效率.
主要方法:
- 对Tide搜索引擎的架构增强.
- 在超过1000万个光谱和70亿个的数据集上进行测试.
- 与MSFragger和Sage.等现有工具进行基准测试.
主要成果:
- 增强的Tide架构可以在商品硬件上处理>1000万个光谱和>70亿个.
- 性能比之前的Tide版本快2至7倍.
- 实现速度与MSFragger和Sage相比,内存要求大大降低.
结论:
- 改进的Tide引擎为大规模蛋白质组数据分析提供了可扩展和高效的解决方案.
- 开源可用性和多平台二进制文件 (Windows,Linux,Mac) 提高了可访问性.
- 解决了当前处理大量MS/MS数据集的局限性.
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