1,721,000 research outputs found
<em><em>i</em></em>coshift:a versatile tool for the rapid alignment of 1D NMR spectra
No full textThe increasing scientific and industrial interest towards metabonomics takes advantage from the high qualitative and quantitative information level of nuclear magnetic resonance (NMR) spectroscopy. However, several chemical and physical factors can affect the absolute and the relative position of an NMR signal and it is not always possible or desirable to eliminate these effects a priori. To remove misalignment of NMR signals a posteriori, several algorithms have been proposed in the literature. The icoshift program presented here is an open source and highly efficient program designed for solving signal alignment problems in metabonomic NMR data analysis. The icoshift algorithm is based on correlation shifting of spectral intervals and employs an FFT engine that aligns all spectra simultaneously. The algorithm is demonstrated to be faster than similar methods found in the literature making full-resolution alignment of large datasets feasible and thus avoiding down-sampling steps such as binning. The algorithm uses missing values as a filling alternative in order to avoid spectral artifacts at the segment boundaries. The algorithm is made open source and the Matlab code including documentation can be downloaded from www.models.life.ku.dk. © 2009 Elsevier Inc. All rights reserved
Simultaneous classification of multiple classes in NMR metabolomics and vibrational spectroscopy using interval-based classification methods:iECVA vs iPLS-DA
No full textInterval based chemometric algorithms have proven to be very powerful for spectral alignments, spectral regressions and spectral classifications. The interval-based methods may not only improve the performance, but also reduce model complexity and enhance the spectral interpretation. Extended Canonical Variate Analysis (ECVA) is a powerful method for multiple group classifications of multivariate data and can easily be extended to an interval approach, iECVA. This study outlines the iECVA method and compares its performance to interval Partial Least Squares Discriminant Analysis (iPLS-DA) on three spectroscopic datasets from Nuclear Magnetic Resonance (NMR), Near Infrared (NIR) and Infrared (IR) spectroscopy, respectively. The results invariantly show that the interval-based classification methods greatly enhance the interpretability of the models by identifying important spectral regions, which facilitate interpretation and biomarker discovery. Although the results for the two methods are similar regarding the number of misclassifications and identified important regions, the model complexity of the PLS-DA proved to consistently lower than the ECVA. The Matlab source codes for both iECVA and iPLS-DA are made freely available at www.models.life.ku.dk
icoshift: an effective tool for the alignment of chromatographic data
No full textThe interval Correlation Optimised shifting algorithm (icoshift) has recently been introduced for the alignment of nuclear magnetic resonance spectra. The method is based on an insertion/deletion model to shift intervals of spectra/chromatograms and relies on an efficient Fast Fourier Transform based computation core that allows the alignment of large data sets in a few seconds on a standard personal computer. The potential of this programme for the alignment of chromatographic data is outlined with focus on the model used for the correction function. The efficacy of the algorithm is demonstrated on a chromatographic data set with 45 chromatograms of 64000 data points. Computation time is significantly reduced compared to the Correlation Optimised Warping (COW) algorithm, which is widely used for the alignment of chromatographic signals. Moreover, icoshift proved to perform better than COW in terms of quality of the alignment (viz. of simplicity and peak factor), but without the need for computationally expensive optimisations of the warping meta-parameters required by COW. Principal Component Analysis (PCA) is used to show how a significant reduction on data complexity was achieved, improving the ability to highlight chemical differences amongst the samples.JRC.I.6 - Systems toxicolog
Investigations of la Rioja terroir for wine production using 1H NMR metabolomics
No full textIn this study, La Rioja wine terroir was investigated by the use of 1H NMR metabolomics on must and wine samples. Rioja is a small wine region in central northern Spain which can geographically be divided into three subareas (Rioja Alta, Rioja Baja, and Rioja Alavesa). The winemaking process from must, through alcoholic and malolactic fermentation, was followed by NMR metabolomics and chemometrics of nine wineries in the Rioja subareas (terroirs). Application of interval extended canonical variate analysis (iECVA) showed discriminative power between wineries which are geographically very close. Isopentanol and isobutanol compounds were found to be key biomarkers for this differentiation. © 2012 American Chemical Society
Chemometric Exploration of Quantitative NMR Data
No full textThis article outlines the synergistic relationship between NMR and chemometrics. The latent variable approach used in chemometrics has proven very powerful for performing inductive explorations of biological systems and for its usefulness insolving industrial problems effectively. This article reviews some of the commonest latent variable approaches applied to the exploratory and predictive modeling of NMR data. It describes how challenging NMR data can be adapted for multivariate data analysis and how the different chemometric methods manipulate the NMR data. The different results from unsupervised data exploration by principal component analysis and multivariate curve resolution are illustrated. On the other hand, many modern applications of NMR within metabolomics and quality control are based on supervised regression analysis or classification analysis. This article demonstrates how these basic chemometric methods work and gives examples of how such methods can be optimized by variable reduction and orthogonal factor extraction. Validation methods and classification performance by the receiver operating characteristics are illustrated. Finally, the potential for merging advanced multiway chemometric methods such as parallel factor analysis (PARAFAC) with the ability of NMR to record true high-order data is emphasized, and illustrated by the application to 2D diffusion-edited spectra of human plasma samples
1H NMR Spectroscopy of Lipoproteins-When Size Matters
No full textLipoproteins are a wide class of biological structures represented by micellar aggregates of biomolecules that allow the fat content to be transported through the hydrophilic blood environment. When analyzing lipoproteins, NMR spectroscopy represents the only analytical platform capable of obtaining signals from their constituent molecules while still structured in the physiological micellar form. In comparison to the UC reference method, NMR spectroscopy boasts drastically shorter times for the analysis and much smaller samples. Furthermore, the manual slicing requested for separating the lipoprotein subclasses in UC, results in larger analytical errors and reproducibility problems which are significantly reduced when NMR analysis is adopted. It is also possible to sensitize the NMR measurements to translational diffusion which can be modelled to achieve an even better definition of the lipoprotein particle distribution. On the downside, the NMR signals from the lipoprotein main constituents, the triglycerides, give rise to very broad overlapping signals, combined by all the contributing lipoprotein subclasses, which cannot be efficiently solved by classical statistical methods. However because of the increased computational power of modern computers, a chemometric approach on the full featured, full resolution NMR spectra has been attempted with great success. The slightly different peak shapes and shifts are modelled in a multivariate fashion providing detailed information on the lipoprotein composition in a continuous fashion. The new NMR-based high-throughput method for lipoprotein profiling has great potential for future nutritional metabolomics studies focused on developing stratified nutrition for different populations. The new iPLS-based method enables extraordinarily fast, inexpensive, and robust prediction of absorption kinetics of chylomicrons. The high-throughput nature of the new lipoprotein profiling method will allow real-time measurements of the return to normal homeostasis after a food challenge and thus provide a much better understanding of food digestion and health than the current static methods. It creates new opportunities for research in lifestyle diseases and obesity, becoming a valuable tool in nutritional research for assessment of absorption of exogenous diet-derived lipid
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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