Department of Computer Science , University of Montana , Missoula , Montana 59801 , United States.
Protein Metrics, Inc. , Cupertino , California 95014 , United States.
J Proteome Res. 2019 Sep 6;18(9):3268-3281. doi: 10.1021/acs.jproteome.9b00216. Epub 2019 Jul 29.
In the metabolomics, glycomics, and mass spectrometry of structured small molecules, the combinatoric nature of the problem renders a database impossibly large, and thus de novo analysis is necessary. De novo analysis requires an alphabet of mass difference values used to link peaks in fragmentation spectra when they are different by a mass in the alphabet divided by a charge. Often, this alphabet is not known, prohibiting de novo analysis. A method is proposed that, given fragmentation mass spectra, identifies an alphabet of / differences that can build large connected graphs from many intense peaks in each spectrum from a collection. We then introduce a novel approach to efficiently find recurring substructures in the de novo graph results.
在代谢组学、糖组学和结构小分子的质谱分析中，问题的组合性质使得数据库变得非常庞大，因此需要从头分析。从头分析需要使用质量差异值的字母表，当碎片谱中的峰相差一个字母表中的质量除以一个电荷时，该字母表用于连接峰。通常，这个字母表是未知的，禁止从头分析。本文提出了一种方法，给定碎片质谱，可以识别出一个 / 差异字母表，该字母表可以从一个集合中每个光谱的许多强烈峰构建大的连通图。然后，我们引入了一种新的方法来有效地发现从头生成的图形结果中的重复子结构。
