网格上质谱蛋白质组学数据的预处理

M. Cannataro, P. Guzzi, T. Mazza, G. Tradigo, P. Veltri
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引用次数: 33

摘要

质谱和数据挖掘的结合使用是蛋白质组学模式分析的一种新方法,用于发现新的生物标志物或识别蛋白质组学图谱中的模式和关联。质谱仪产生的数据受到样品制备和仪器近似的误差和噪声的影响,因此在进行分析之前需要采用不同的预处理技术。我们调查了不同的光谱预处理技术,并提出了一个软件工具的第一个设计,该软件工具允许在网格上对质谱数据进行预处理、管理和分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Preprocessing of mass spectrometry proteomics data on the grid
The combined use of mass spectrometry and data mining is a novel approach in proteomic pattern analysis for discovering novel biomarkers or identifying patterns and associations in proteomic profiles. Data produced by mass spectrometers are affected by errors and noise due to sample preparation and instrument approximation, so different preprocessing techniques need to be applied before analysis is conducted. We survey different techniques for spectra preprocessing, and we present a first design of a software tool that allows the preprocessing, management and analysis of mass spectrometry data on the Grid.
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