LIMPIC: a computational method for the separation of protein MALDI-TOF-MS signals from noise.
LIMPIC: a computational method for the separation of protein MALDI-TOF-MS signals from noise.
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DOI：
10.1186/1471-2105-8-101
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发表时间：
2007-03-26
影响因子：
3
通讯作者：
Urbani A
中科院分区：
文献类型：
--
作者：
Mantini D;Petrucci F;Pieragostino D;Del Boccio P;Di Nicola M;Di Ilio C;Federici G;Sacchetta P;Comani S;Urbani A
质谱学蛋白质图谱是临床蛋白质组学中发现生物标志物的一种很有前途的工具。然而，需要开发一种可靠的方法将蛋白质信号从噪声中分离出来。本文提出了一种从线性MALDI-TOF数据中检测蛋白质峰的计算方法LIMPIC。LIMPIC基于降低背景噪声和消除基线的新技术。峰值检测是在考虑质谱图中存在非均匀噪声电平的情况下执行的。使用从多个光谱收集的峰值的比较来基于检测率参数对它们进行分类，从而将蛋白质信号与其他干扰分开。LIMPIC前处理技术优于其他经典的前处理技术，能够可靠地分解MALDI-TOF质谱图中的背景噪声和基线漂移。它提供了与峰值强度相关的较低的变异系数，提高了可以从单一光谱提取的信息的可靠性。我们的结果表明，即使在低蛋白质浓度的区域，LIMPIC拾峰算法也是有效的。与商业软件和免费软件峰值提取算法的分析比较表明，无论是在体外纯化的蛋白质样本还是在人体血浆样本上，该算法都具有优越的灵敏度和特异度。LIMPIC提取的峰强度的定量信息可以通过先进的统计工具用于识别有意义的蛋白质谱：LIMPIC在生物标志物发现的角度可能有价值。
Mass spectrometry protein profiling is a promising tool for biomarker discovery in clinical proteomics. However, the development of a reliable approach for the separation of protein signals from noise is required. In this paper, LIMPIC, a computational method for the detection of protein peaks from linear-mode MALDI-TOF data is proposed. LIMPIC is based on novel techniques for background noise reduction and baseline removal. Peak detection is performed considering the presence of a non-homogeneous noise level in the mass spectrum. A comparison of the peaks collected from multiple spectra is used to classify them on the basis of a detection rate parameter, and hence to separate the protein signals from other disturbances. LIMPIC preprocessing proves to be superior than other classical preprocessing techniques, allowing for a reliable decomposition of the background noise and the baseline drift from the MALDI-TOF mass spectra. It provides lower coefficient of variation associated with the peak intensity, improving the reliability of the information that can be extracted from single spectra. Our results show that LIMPIC peak-picking is effective even in low protein concentration regimes. The analytical comparison with commercial and freeware peak-picking algorithms demonstrates its superior performances in terms of sensitivity and specificity, both on in-vitro purified protein samples and human plasma samples. The quantitative information on the peak intensity extracted with LIMPIC could be used for the recognition of significant protein profiles by means of advanced statistic tools: LIMPIC might be valuable in the perspective of biomarker discovery.
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影响因子：
5.6
作者：
Bonk, T;Humeny, A
通讯作者：
Humeny, A
影响因子：
3
作者：
Fushiki, Tadayoshi;Fujisawa, Hironori;Eguchi, Shinto
通讯作者：
Eguchi, Shinto
影响因子：
3.4
作者：
Biroccio, A;del Boccio, P;Urbani, A
通讯作者：
Urbani, A
影响因子：
7.4
作者：
SAVITZKY, A;GOLAY, MJE
通讯作者：
GOLAY, MJE
DOI：
10.1016/s0169-7439(03)00113-8
发表时间：
2003-11-28
影响因子：
3.9
作者：
Jarman, KH;Daly, DS;Wahl, KL
通讯作者：
Wahl, KL