MRUniNovo: an efficient tool for de novo peptide sequencing utilizing the hadoop distributed computing framework
MRUniNovo: an efficient tool for de novo peptide sequencing utilizing the hadoop distributed computing framework
复制标题
MRUniNovo：利用 hadoop 分布式计算框架进行从头肽测序的高效工具
DOI：
10.1093/bioinformatics/btw721
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发表时间：
2017-03-15
期刊：
影响因子：
5.8
通讯作者：
Li, Kenli
中科院分区：
文献类型：
--
作者：
Li, Chuang;Chen, Tao;Li, Kenli
基于串联质谱的从头肽测序是一个复杂且耗时的过程。当前的从头肽测序算法无法快速、彻底地处理大型质谱数据集。在本文中，我们提出了MRUniNovo，一种新的工具，用于并行从头肽测序。MRUniNovo基于Hadoop计算平台并行化UniNovo。我们的实验结果表明，MRUniNovo显着减少了从头肽测序的计算时间，而不会牺牲结果的正确性和准确性，因此可以处理UniNovo无法处理的非常大的数据集。
Tandem mass spectrometry-based de novo peptide sequencing is a complex and time-consuming process. The current algorithms for de novo peptide sequencing cannot rapidly and thoroughly process large mass spectrometry datasets. In this paper, we propose MRUniNovo, a novel tool for parallel de novo peptide sequencing. MRUniNovo parallelizes UniNovo based on the Hadoop compute platform. Our experimental results demonstrate that MRUniNovo significantly reduces the computation time of de novo peptide sequencing without sacrificing the correctness and accuracy of the results, and thus can process very large datasets that UniNovo cannot.