Wavelet- and Fourier-transform-based spectrum similarity approaches to compound identification in gas chromatography/mass spectrometry.

Wavelet- and Fourier-transform-based spectrum similarity approaches to compound identification in gas chromatography/mass spectrometry.
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DOI:
10.1021/ac200740w
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发表时间:
2011-07-15
影响因子:
7.4
通讯作者:
Kim, Seongho
Kim, Seongho
中科院分区:
化学1区
文献类型:
--
作者:
Koo, Imhoi;Zhang, Xiang;Kim, Seongho

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高通量气相色谱-质谱(GC-MS)技术为分析大量化学和生物样品提供了强有力的手段。GC-MS数据的重要分析之一是化合物鉴定。本文提出了一种基于离散小波和傅立叶变换的光谱相似性度量方法。所提出的方法是由加权强度和小波/傅立叶系数使用余弦相关的复合相似。所提出的方法沿着与现有的相似性措施的性能进行了评价,使用NIST化学WebBook质量数据库维护的美国国家标准与技术研究所(NIST)作为参考光谱和重复质谱数据库查询光谱。分析结果表明,基于小波/傅立叶变换的方法的识别精度分别提高了2.02%和1.95%,相比加权点积(余弦相关)和3.01%和3.08%,分别相比,复合相似性度量。改进的识别精度表明,所提出的方法优于现有的相似性措施在文献中。
The high-throughput gas chromatography-mass spectrometry (GC-MS) technology offers a powerful means of analyzing a large number of chemical and biological samples. One of the important analyses of GC-MS data is compound identification. In this work, novel spectral similarity measures based on the discrete wavelet and Fourier transforms were proposed. The proposed methods are composite similarities that are composed of weighted intensities and wavelet/Fourier coefficients using cosine correlation. The performance of the proposed approaches along with the existing similarity measures was evaluated using the NIST Chemistry WebBook mass database maintained by the National Institute of Standards and Technology (NIST) as a library of reference spectra and repetitive mass spectral data as query spectra. The analysis results showed that the identification accuracies of the wavelet/Fourier transform-based methods were improved by 2.02% and 1.95%, respectively, comparing the weighted dot product (cosine correlation) and by 3.01% and 3.08%, respectively, comparing to the composite similarity measure. The improved identification accuracy demonstrates that the proposed approaches outperformed the existing similarity measures in the literature.
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