Winners of CASMI2013: Automated Tools and Challenge Data.
Winners of CASMI2013: Automated Tools and Challenge Data.
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DOI：
10.5702/massspectrometry.s0039
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发表时间：
2014-01-01
期刊：
影响因子：
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通讯作者：
Yamamoto, Atsushi
中科院分区：
文献类型：
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作者：
Nishioka, Takaaki;Kasama, Takeshi;Yamamoto, Atsushi
CASMI（Critical Assessment of Small Molecule Identification）是一项竞赛，参赛者使用盲质谱作为挑战数据来识别挑战分子的分子式和化学结构。七个研究团队参加了CASMI 2013。CASMI 2013的赢家是美国伊利诺伊大学芝加哥分校的Andrew Newsome和Dejan Nikolic团队。该团队通过手动解释挑战数据并通过搜索内部和公共质谱数据库以及化学物质和文献数据库，在16种挑战分子中确定了15种。MAGMa被选为CASMI 2013最佳自动化工具。在一些挑战中，大多数自动化工具成功识别了挑战分子，与化合物类别和分子量大小无关。在这些挑战数据中，观察到鉴别所必需的所有同位素峰和产物离子均在预期质量准确度范围内。在其他挑战中，大多数自动化工具都失败了，或者识别出了候选解决方案以及许多假阳性候选解决方案。然后，我们根据质谱的质量、解离机制以及挑战分子的化合物类别和元素组成分析了这些挑战数据。
CASMI (Critical Assessment of Small Molecule Identification) is a contest in which participants identify the molecular formula and chemical structure of challenging molecules using blind mass spectra as the challenge data. Seven research teams participated in CASMI2013. The winner of CASMI2013 was the team of Andrew Newsome and Dejan Nikolic, the University of Illinois at Chicago, IL, USA. The team identified 15 among 16 challenge molecules by manually interpreting the challenge data and by searching in-house and public mass spectral databases, and chemical substance and literature databases. MAGMa was selected as the best automated tool of CASMI2013. In some challenges, most of the automated tools successfully identified the challenge molecules, independent of the compound class and magnitude of the molecular mass. In these challenge data, all of the isotope peaks and the product ions essential for the identification were observed within the expected mass accuracy. In the other challenges, most of the automated tools failed, or identified solution candidates together with many false-positive candidates. We then analyzed these challenge data based on the quality of the mass spectra, the dissociation mechanisms, and the compound class and elemental composition of the challenge molecules.