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  • 标题:Improved De Novo Peptide Sequencing using LC Retention Time Information
  • 本地全文:下载
  • 作者:Yves Frank ; Tomas Hruz ; Thomas Tschager
  • 期刊名称:LIPIcs : Leibniz International Proceedings in Informatics
  • 电子版ISSN:1868-8969
  • 出版年度:2017
  • 卷号:88
  • 页码:26:1-26:17
  • DOI:10.4230/LIPIcs.WABI.2017.26
  • 出版社:Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
  • 摘要:Liquid chromatography combined with tandem mass spectrometry (LC-MS/MS) is an important tool in proteomics for identifying the peptides in a sample. Liquid chromatography temporally separates the peptides and tandem mass spectrometry analyzes the peptides, that elute one after another, by measuring their mass-to-charge ratios and the mass-to-charge ratios of their prefix and suffix fragments. De novo peptide sequencing is the problem of reconstructing the amino acid sequences of the analyzed peptide from this measurement data. While previous approaches solely consider the mass spectrum of the fragments for reconstructing a sequence, we propose to also exploit the information obtained from liquid chromatography. We study the problem of computing a sequence that is not only in accordance with the experimental mass spectrum, but also with the retention time of the separation by liquid chromatography. We consider three models for predicting the retention time of a peptide and develop algorithms for de novo sequencing for each model. An evaluation on experimental data from synthesized peptides for two of these models shows an improved performance compared to not using the chromatographic information.
  • 关键词:Computational proteomics; Peptide identification; Mass spectrometry; De novo peptide sequencing; Retention time prediction
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