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评估肽段从头测序算法在大型多样数据集上的性能。

Assessing peptide de novo sequencing algorithms performance on large and diverse data sets.

作者信息

Pitzer Erik, Masselot Alexandre, Colinge Jacques

机构信息

Bioinformatics Department, Upper Austria University of Applied Sciences at Hagenberg, Hagenberg, Austria.

出版信息

Proteomics. 2007 Sep;7(17):3051-4. doi: 10.1002/pmic.200700224.

Abstract

De novo peptide sequencing algorithms are often tested on relatively small data sets made of excellent spectra. Since there are always more and more tandem mass spectra available, we have assembled six large, reliable, and diverse (three mass spectrometer types) data sets intended for such tests and we make them accessible via a web server. To exemplify their use we investigate the performance of Lutefisk, PepNovo, and PepNovoTag, three well-established peptide de novo sequencing programs.

摘要

从头肽测序算法通常在由优质光谱组成的相对较小的数据集上进行测试。由于可用的串联质谱越来越多,我们已经组装了六个大型、可靠且多样(三种质谱仪类型)的数据集用于此类测试,并通过网络服务器使其可供访问。为了举例说明它们的用途,我们研究了Lutefisk、PepNovo和PepNovoTag这三个成熟的肽从头测序程序的性能。

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