A computational platform for MALDI-TOF mass spectrometry data: Application to serum and plasma samples
A computational platform for MALDI-TOF mass spectrometry data: Application to serum and plasma samples
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DOI：
10.1016/j.jprot.2009.11.004
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发表时间：
2010-01-03
影响因子：
3.3
通讯作者：
Urbani, Andrea
中科院分区：
文献类型：
--
作者：
Mantini, Dante;Petrucci, Francesca;Urbani, Andrea
背景：质谱分析（MS）正成为生物标志物发现的金标准。针对这一应用，已经提出了几种基于质谱的生物信息学方法，但不同研究小组对相同质谱数据的研究结果存在差异，这表明可靠方法的定义尚未确定。在这项工作中，我们提出了一个集成软件平台MASCAP，旨在从基质辅助激光解吸电离飞行时间质谱（MALDI - TOF MS）数据中进行比较性生物标志物检测。
结果：MASCAP集成了去噪和特征提取算法，这些算法已被证明能在质谱图中提供一致的峰；此外，它依靠统计分析和图形工具来比较组间结果。使用MALDI - TOF数据以及表面增强激光解吸电离飞行时间质谱（SELDI - TOF）数据证明了其在质谱处理方面的有效性。通过比较来自同一临床人群的血清和血浆样本的MALDI - TOF质谱图，展示了其在检测潜在蛋白质生物标志物方面的有用性。
结论：MASCAP中实施的分析方法通过辅助识别疾病的蛋白质组表达特征，可能简化生物标志物的检测。该软件的MATLAB实现以及用于验证的数据可在http://www.unich.it/proteomica/bioinf获取。（C）2009爱思唯尔有限公司。保留所有权利。
Background: Mass spectrometry (MS) is becoming the gold standard for biomarker discovery. Several MS-based bioinformatics methods have been proposed for this application, but the divergence of the findings by different research groups on the same MS data suggests that the definition of a reliable method has not been achieved yet. In this work, we propose an integrated software platform, MASCAP, intended for comparative biomarker detection from MALDI-TOF MS data.Results: MASCAP integrates denoising and feature extraction algorithms, which have already shown to provide consistent peaks across mass spectra; furthermore, it relies on statistical analysis and graphical tools to compare the results between groups. The effectiveness in mass spectrum processing is demonstrated using MALDI-TOF data, as well as SELDI-TOF data. The usefulness in detecting potential protein biomarkers is shown comparing MALDI-TOF mass spectra collected from serum and plasma samples belonging to the same clinical population. Conclusions: The analysis approach implemented in MASCAP may simplify biomarker detection, by assisting the recognition of proteomic expression signatures of the disease. A MATLAB implementation of the software and the data used for its validation are available at http://www.unich.it/proteomica/bioinf. (C) 2009 Elsevier B.V. All rights reserved.