化学计量学方法在脂质组学数据解析中的应用

脂质组学是依赖于分析技术而发展的一门新兴学科,用于全面表征与基因调控、蛋白表达、脂质代谢密切相关的脂质分子,揭示脂质在各种生命活动中的作用机制和代谢途径网络。随着质谱及其联用技术进一步发展和完善,脂质组学逐渐向快速、自动化和高通量的方向发展,而大规模的脂质组数据分析已成为脂质组学研究领域的一大难点。化学计量学主要应用于脂质组学中的基线校正和背景扣除、信号峰识别、同位素分布解析、统计分析等过程,因此,基于化学计量学方法的脂质组学数据自动化解析策略成为研究者关心的热点。该文对近年来化学计量学在脂质组学数据解析中的应用进行了综述,并对基于化学计量学的脂质组学数据解析的未来发展进行了展望。     

基于化学计量学的GC-MS分析方法研究

气相色谱-质谱联用(GC-MS)、液相色谱-质谱联用(LC-MS)等,为分析多组分混合物提供了有力手段并广泛地应用于化工、食品、生物、医药等领域.但在分析多组分复杂体系时,其色谱信号严重重叠,使得该方法难于进行准确的定性定量分析.化学计量学方法的引入,为解决该问题提供了一种新手段.例如化学因子分析(CFA)、多元校正解析方法(MCR)、免疫算法(IA)和小波变换(WT)等已被成功地运用于复杂体系分析化学重叠信号的解析.     

免疫算法: 一种新的多组分重叠色谱信号的解析方法

色谱及其联用技术的快速发展使其成为复杂样品分析的重要手段,但在复杂样品分析中仍难以避免多组分色谱信号的重叠。化学计量学利用数学方法对复杂重叠信号进行解析,为复杂样品的色谱分析提供了新的手段。本文对免疫算法研究的近期进展进行了总结,并以具体的实例介绍了其在多组分重叠色谱信号解析方面的应用。     

三维(二阶)算法在液相色谱分析中的应用

使用"垂线法"、"切线法"或"三角形法"等传统方法对液相色谱重叠峰分辨时经常会遇到误差过大的情况,而使用三维(二阶)算法对重叠和拖尾峰分辨可以最大限度地降低这种因几何分割而人为产生的误差。这样改进的色谱解析方法具有自动化程度高、抗干扰能力强、对重叠/拖尾峰定量准确等优点,甚至可以减少样品前处理和色谱条件优化。该方法的核心是基于化学计量学三维(二阶)算法抽取有效信息和建模的思想,三维色谱数据按照对三线性模型的符合程度有"三线性数据"和"非三线性数据"的区别,相应地将三维(二阶)算法分为"三线性算法"和"非三线性算法"。本文综述了近10年来国内外三维(二阶)算法在复杂体系液相色谱分析中的应用进展,侧重于样品前处理、辅助算法、校正算法间的联用和对比等问题。     

近红外光谱分析中的化学计量学算法研究新进展

近红外光谱是一种绿色、快捷的分析技术,在科学研究、工业生产以及日常检测中得到广泛应用。化学计量学算法的应用在近红外光谱技术的发展过程中发挥了重要作用。化学计量学方法通过寻找测量变量之间的相关性,构建数学模型,量化样本间的差异性,并发现事物变化的内在规律,实现较合理准确的未知预测。这也是"大数据"战略的重要环节和主旨所在。该文针对近红外光谱吸收信号较弱、谱峰重叠严重,以及光谱测量过程中易受背景、噪声、无信息变量和外界环境因素干扰等,导致借助化学计量学方法建立的光谱与研究目标的定性定量分析模型变差问题,总结了近年来在近红外光谱领域所提出的一些化学计量学新方法,包括光谱预处理、变量选择、多元校正和模型转移,从不同角度阐述了这些方法在消除近红外光谱模型的干扰因素,提高模型的可靠性、预测准确性和适用性等方面的作用。     

分析化学计量学的若干新进展

对分析化学计量学的若干新进展进行了讨论, 侧重从作者实验室所进行的研究工作的视角论述了高维数据的分辨、用于化学信号处理的形态学理论和方法、解决复杂化学问题的多元校正和化学模式识别以及联用色谱仪二维数据的分辨新方法的发展.     

多维联用色谱及其数据处理和应用

多维联用色谱是一种基于色谱分离与光谱检测联用的新型分析手段,其数据处理涉及许多矩阵分解的数学理论算法。本文对多维联用色谱的概念、化学计量学数据处理以及多维联用色谱在复杂分析体系中的实际应用进行介绍。     

非负矩阵因子分解法分析苍术的气相色谱-质谱重叠峰

非负矩阵因子分解(non-negative matrix factorization,NMF)是对非负数据处理的一种多元统计分析方法.NMF分解结果没有"负值",易于理解和解释,具有比较明确的物理化学意义.由于其多解的特征,文献介绍的NMF算法并不能直接用于化学混合信号解析.作者根据化学波谱的基本特征(化学波谱的平滑性、色谱的单峰性以及质谱的稀疏性)对NMF算法进行了改进,缩小了其多解范围.应用改进的NMF进行模拟HPLC-DAD型两维数据(其中色谱严重重叠和完全重叠)和苍术GC/MS实验数据解析,得到了比较理想的结果.实验表明,改进后的NMF是一个可用于复杂样品化学信号分析的化学计量学新方法.     

基于超高效液相色谱-高分辨质谱的非靶向代谢组学技术结合化学计量学对信阳茶树品种差异的研究

基于超高效液相色谱联用高分辨质谱(UHPLC-HRMS)的非靶向代谢组学技术结合化学计量学自动化数据分析策略,分析了信阳地区乌牛早、舒茶早、白毫早、平阳特早、陕茶一号共5个茶树品种的化学成分差异.采用自动化解析方法软件平台对仪器采集的原始信号直接解析,共鉴定出生物碱、儿茶素、酚酸、氨基酸、核苷及黄酮类物质等33种差异性...     

非负矩阵因子分解法分析苍术的气相色谱-质谱重叠峰

非负矩阵因子分解（non-negative matrix factorization，NMF）是对非负数据处理的一种多元统计分析方法。NMF分解结果没有“负值”，易于理解和解释，具有比较明确的物理化学意义。由于其多解的特征，文献介绍的NMF算法并不能直接用于化学混合信号解析。作者根据化学波谱的基本特征（化学波谱的平滑性、色谱的单峰性以及质谱的稀疏性）对NMF算法进行了改进，缩小了其多解范围。应用改进的NMF进行模拟HPLC-DAD型两维数据（其中色谱严重重叠和完全重叠）和苍术GC／MS实验数据解析，得到了比较理想的结果。实验表明，改进后的NMF是一个可用于复杂样品化学信号分析的化学计量学新方法。     

Chemometric methods for evaluation of chromatographic separation quality from two-way data--a review

Most traditional chromatographic separation criteria or response functions are defined on chromatograms recorded by single-channel detectors, e.g. a spectrometer measuring the absorbance at a single wavelength or a thermal conductivity detector. When the peaks are seriously overlapped, usually there is a lack of the information concerning the total number of chemical components, overlap degree of the peaks and peak purity. Such information characterizes some crucial aspects of separation process and lack of it will lead to an inaccurate and misleading evaluation of separation quality as well as some computational ambiguity for many traditional response functions. In contrast, hyphenated chromatography-(multi-channel) spectroscopy instruments together with chemometric methods will largely increase the information content available in chromatographic detection. Such information, if properly used, can cast a new light on evaluation of chromatographic separation quality. The main objective of this article is to review chemometric methods devoted to estimation of the number of chemical components, determination of elution sequence and assessment of peak purity. Some newly defined response functions or separation criteria based on extracted information by chemometric methods are also introduced. The methods reviewed are limited to those for treating two-way data obtained by hyphenation of high-performance liquid chromatography with multi-channel detectors. We prefer to provide a comprehensive view of such methods rather than present a full list of all the methods developed. Further details of some important methods are touched upon in favor of employment and understanding of them by researchers not very familiar with chemometrics.     

Chemometrics in pharmaceutical analysis: an introduction, review, and future perspectives

Chemometrics is the application of statistical and mathematical methods to analytical data to permit maximum collection and extraction of useful information. The utility of chemometric techniques as tools enabling multidimensional calibration of selected spectroscopic, electrochemical, and chromatographic methods is demonstrated. Application of this approach mainly for interpretation of UV-Vis and near-IR (NIR) spectra, as well as for data obtained by other instrumental methods, makes identification and quantitative analysis of active substances in complex mixtures possible, especially in the analysis of pharmaceutical preparations present in the market. Such analytical work is carried out by the use of advanced chemical instruments and data processing, which has led to a need for advanced methods to design experiments, calibrate instruments, and analyze the resulting data. The purpose of this review is to describe various chemometric methods in combination with UV-Vis spectrophotometry, NIR spectroscopy, fluorescence spectroscopy, electroanalysis, chromatographic separation, and flow-injection analysis for the analysis of drugs in pharmaceutical preparations. Theoretical and practical aspects are described with pharmaceutical examples of chemometric applications. This review will concentrate on gaining an understanding of how chemometrics can be useful in the modern analytical laboratory. A selection of the most challenging problems faced in pharmaceutical analysis is presented, the potential for chemometrics is considered, and some consequent implications for utilization are discussed. The reader can refer to the citations wherever appropriate.     

Characterization of essential oil components of Iranian geranium oil using gas chromatography-mass spectrometry combined with chemometric resolution techniques

The essential oil components of geranium oil cultivated in center of Iran were identified and determined using gas chromatography-mass spectrometry data combined with the chemometric resolution techniques. A total of 61 components accounting for 91.51% were identified using similarity searches between the mass spectra and MS database. This number was extended to 85 components using chemometric techniques. Various chemometric methods such as morphological scores, simplified Borgen method (SBM) and fixed size moving window evolving factor analysis (FSMWEFA) were used for determining the number of components, pure variables, zero concentration and selective regions. Then the overlapping peak clusters were resolved into pure chromatograms and pure mass spectra using heuristic evolving latent projections (HELP) method. A characteristic feature of the Iranian geranium oil is the absence of 10-epi-gamma-eudesmol in its constituents compared with the oil from northern and southern parts of India. The results of this work show that combination of hyphenated chromatographic methods and resolution techniques provide a complementary method for accurate analysis of essential oils.     

联用色谱数据的双窗口因子分析

利用组分光谱的特征信息,发展了一种能直接对联用色谱重叠峰中组分进行定性定量分析的新方法──双窗口因子分析（dualwindowfactoranalysis,DWPA）。该法可从多组分重叠峰中定性目标组分,且在未经其它组分的分辨下可直接对目标组分的光谱、色谱进行分辨。因此更适应于联用色谱对复杂体系中待测组分的定性定量分析。用该法成功地对4组分重叠峰进行了分析,实验结果令人满意。     

Rapid analysis of multicomponent pesticide mixture by GC-MS with the aid of chemometric resolution

Applications of hyphenated chromatographic techniques, especially GC-MS technique, have been reported in chemical, biological, environmental, agricultural and medical analysis. The complexity of the samples in these fields is still an obstacle for the technique to be practical and the overlapping of the multicomponent signals induces chemometric methods widely employed. In this work, taking the rapid analysis of pesticide mixture as an example, a chemometric approach was proposed for resolution of multicomponent overlapping GC-MS signal. In the method, a mass spectral library of pesticides was organized at first, then target factor analysis (TFA) was employed for testing the existence of a specific pesticide in the multicomponent overlapping GC-MS signal, and finally the chromatographic information of the pesticide was extracted by a non-negative immune algorithm (IA). A GC-MS signal of a 40-component pesticide mixture eluted within 9 min was analyzed by the method. It was found that the mass spectra and chromatographic profiles of almost all the pesticides can be obtained.     

Chemometrics for the analysis of chromatographic data in metabolomics investigations

Metabolomics aims to better understand biological systems through the chemical analysis of an organism's metabolic profile. One common method of analysis is mass spectrometry preceded by chromatographic separations. Samples produced by metabolomics investigations can contain hundreds to thousands of compounds, which can put great strain on the instrumental analysis. In order to improve these analyses, the data analysis must not be overlooked. The ever‐evolving field of chemometrics provides many useful tools for the analysis of chromatographic data. These include methods for preprocessing data to extract a maximum amount of information from the data as well as pattern recognition in order to find the compounds that vary the most in relation to the perturbation to the biological system under study. This article aims to highlight and provide future outlooks on current chemometric methods for chromatographic‐based metabolomics investigations. Copyright © 2014 John Wiley & Sons, Ltd.     

Start-to-end processing of two-dimensional gel electrophoretic images

Gel electrophoresis serves as a basic analytical tool in the proteomic studies. However, processing of gel electrophoretic images is still the main bottleneck of data analysis, and there is an increasing need for the fully automated approaches. The proposed start-to-end strategy of analyzing the gel images consists of chemometric tools, which allow their effective preprocessing, automatic warping, and data modeling. The image preprocessing techniques: denoising in the wavelet domain and the penalized asymmetric least squares approach for the background estimation are proposed. Matching of images is based on fuzzy warping of features, extracted from the gel images. For the classification or calibration purpose, multivariate approaches such, as partial least squares (PLS) or kernel-PLS methods are used. Performance of the proposed strategy is demonstrated on the real set of the two-dimensional gel images.     

Chemometrics and modernization of traditional Chinese medicine

Development of chromatographic fingerprinting and its related chemometric methods in the research of quality control of traditional Chinese medicines(TCMs) are discussed. The quality control methods for guarantying the authentication and stability of products and semi-products of TCMs are firstly assessed. The technique based on chromatographic fingerprinting is essentially a kind of high-through put and integral tools to explore the complexity of herbal medicines. In order to further control the comprehensive quality of TCMs,confirmation and identification of their important chemical components are necessary. Some new strategies are proposed to trace the chemical changes of chromatographic fingerprints both in product processing and/or after their administration by modern chromatographic techniques and chemometrics. Combined with systems biology and bioinformatics,it seems possible for one to reveal the working mechanism of TCMs and to further control their intrinsic quality comprehensively.