MS Amanda, a universal identification algorithm optimized for high accuracy tandem mass spectra.
MS Amanda, a universal identification algorithm optimized for high accuracy tandem mass spectra.
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DOI：
10.1021/pr500202e
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发表时间：
2014-08-01
影响因子：
4.4
通讯作者：
Mechtler, Karl
中科院分区：
文献类型：
--
作者：
Dorfer, Viktoria;Pichler, Peter;Stranzl, Thomas;Stadlmann, Johannes;Taus, Thomas;Winkler, Stephan;Mechtler, Karl
关键词：
现代串联质谱仪提供的高精度光谱为分析复杂性增加的蛋白质组样品提供了相当大的优势。在其他因素中，可靠鉴定的肽的数量受到肽鉴定算法的显著影响。虽然最广泛使用的搜索引擎时，高分辨率质谱数据不容易获得碎片离子质量，我们设计了一个评分算法，特别适合于高质量的准确性。我们的算法MS阿曼达通常适用于HCD、ETD和CID碎片类型数据。在检查的高质量准确度数据集上，该算法以相同的错误发现率自信地解释了比Mascot或SEQUEST更多的光谱，对于大多数光谱，Mascot或SEQUEST也解释了极好的重叠和相同的肽序列鉴定。MS阿曼达，可在，是免费提供的独立版本集成到自定义工作流程和作为一个插件的蛋白质组发现者平台。
Today’s highly accurate spectra provided by modern tandem mass spectrometers offer considerable advantages for the analysis of proteomic samples of increased complexity. Among other factors, the quantity of reliably identified peptides is considerably influenced by the peptide identification algorithm. While most widely used search engines were developed when high-resolution mass spectrometry data were not readily available for fragment ion masses, we have designed a scoring algorithm particularly suitable for high mass accuracy. Our algorithm, MS Amanda, is generally applicable to HCD, ETD, and CID fragmentation type data. The algorithm confidently explains more spectra at the same false discovery rate than Mascot or SEQUEST on examined high mass accuracy data sets, with excellent overlap and identical peptide sequence identification for most spectra also explained by Mascot or SEQUEST. MS Amanda, available at , is provided free of charge both as standalone version for integration into custom workflows and as a plugin for the Proteome Discoverer platform.
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影响因子：
9.9
作者：
通讯作者：
--
DOI：
10.1074/mcp.m111.011015
发表时间：
2011-09
期刊：
Molecular & cellular proteomics : MCP
影响因子：
--
作者：
Michalski A;Damoc E;Hauschild JP;Lange O;Wieghaus A;Makarov A;Nagaraj N;Cox J;Mann M;Horning S
通讯作者：
Horning S
影响因子：
9.9
作者：
通讯作者：
--
影响因子：
4.4
作者：
Cox, Juergen;Neuhauser, Nadin;Mann, Matthias
通讯作者：
Mann, Matthias
影响因子：
14.8
作者：
Koecher, Thomas;Pichler, Peter;Mechtler, Karl
通讯作者：
Mechtler, Karl