Processing and Modeling of Nuclear Magnetic Resonance (NMR) Metabolic Profiles

Methods in Molecular Biology

Volumn 708, Issue , 2011, Pages 365-388

  Ebbels, Timothy M D ^a   Lindon, John C ^a   Coen, Muireann ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

CLASSY; genetic algorithms; hierarchical clustering; normalization; PCA; PLS; Preprocessing; scaling; self organizing maps; STOCSY

Indexed keywords

CLIMATE MODEL; CROSS VALIDATION; DECONVOLUTION; GENETIC ALGORITHM; HIERARCHICAL CLUSTERING; IN VITRO STUDY; INTERMETHOD COMPARISON; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY; PARTIAL LEAST SQUARES REGRESSION; PRINCIPAL COMPONENT ANALYSIS; STRUCTURE ANALYSIS; SYSTEMS BIOLOGY; ALGORITHM; ANIMAL; ARTICLE; CLUSTER ANALYSIS; DISCRIMINANT ANALYSIS; INSTRUMENTATION; METABOLOME; METABOLOMICS; METHODOLOGY; RAT; REGRESSION ANALYSIS; REPRODUCIBILITY; SPRAGUE DAWLEY RAT; STATISTICAL MODEL; STATISTICS;

ALGORITHMS; ANIMALS; CLUSTER ANALYSIS; DISCRIMINANT ANALYSIS; LEAST-SQUARES ANALYSIS; MAGNETIC RESONANCE SPECTROSCOPY; METABOLOME; METABOLOMICS; MODELS, STATISTICAL; PRINCIPAL COMPONENT ANALYSIS; RATS; RATS, SPRAGUE-DAWLEY; REPRODUCIBILITY OF RESULTS; STATISTICS AS TOPIC;

EID: 79953754310     PISSN: 10643745     EISSN: 19406029     Source Type: Book Series    
DOI: 10.1007/978-1-61737-985-7_21     Document Type: Chapter

References (39)

1. Lindon, J. C., et al. (2005) The consortium for metabonomic toxicology (COMET): aims, activities and achievements. Pharmacogenomics 6, 691–699.
2. Ebbels, T. M. D. et al. (2007) Prediction and classification of drug toxicity using probabilistic modeling of temporal metabolic data: the consortium on metabonomic toxicology screening approach. J Proteome Res 6, 4407–4422.
3. Ellis, J. K. et al (2009) Effect of the histone deacetylase inhibitor trichostatin a on the metabolome of cultured primary hepatocytes. J Proteome Res 9(1), 413–419.
4. Claridge, T. D. W. (2009) High-resolution NMR techniques in organic chemistry, in (Baldwin, J., Williams, R. M., Backvall, J.-E., eds.), Tetrahedron Organic Chemistry, 2nd ed., Vol. 27, Elsevier Science, Amsterdam, p. 398.
5. Nicholson, J. K., et al. (1989) High-resolution proton magnetic-resonance spectroscopy of biological-fluids. Prog Nucl Magn Reson Spectrosc 21, 449–501.
6. Lindon, J. C., et al. (2001) Pattern recognition methods and applications in biomedical magnetic resonance. Prog Nucl Magn Reson Spectrosc 39, 1.
7. 1 H NMR metabolomics data. Anal Chem 78, 4430– 4442.
8. Lewis, I. A., et al. (2007) Method for determining molar concentrations of metabolites in complex solutions from two-dimensional H-1-C-13 NMR spectra. Anal Chem 79, 9385–9390.
9. Cloarec, O., et al. (2005) Evaluation of the orthogonal projection on latent structure model limitations caused by chemical shift variability and improved visualization of biomarker changes in 1 h NMR spectroscopic metabonomic studies. Anal Chem 77, 517.
10. 1 H nuclear-magnetic-resonance spectra of human urine from normal and pathological states. Anal Biochem 220, 284.
11. Spraul, M., et al. (1994) Automatic reduction of NMR spectroscopic data for statistical and pattern recognition classification of samples. J Pharm Biomed Anal 12, 1215–1225.
12. Ebbels, T. M. D. et al. (2004) Methods for Spectral Analysis and Their Applications: Spectral Replacement, United States.
13. Antoine, J.-P., et al. (2000) Water peak suppression: time-frequency vs time-scale approach. J Magn Res 144, 189–194.
14. Csenki, L., et al. (2007) Proof of principle of a generalized fuzzy hough transform approach to peak alignment of one-dimensional 1 h NMR data. Anal Bioanal Chem 389, 875–885.
15. Veselkov, K., et al. (2009) Recursive segment-wise peak alignment of biological 1 h NMR spectra for improved metabolic biomarker recovery. Anal Chem 81, 56–66.
16. Craig, A., et al. (2006) Scaling and normalization effects in NMR spectroscopic metabonomic data sets. Anal Chem 78, 2262–2267.
17. Dieterle, F., et al. (2006) Probabilistic quotient normalization as robust method to account for dilution of complex biological mixtures. Application in H-1 NMR metabonomics. Anal Chem 78, 4281–4290.
18. Torgrip, R. J. O., et al. (2008) A note on normalization of biofluid 1d H-1-NMR data. Metabolomics 4, 114–121.
19. Durbin, B. P., et al. (2002) A variance-stabilizing transformation for gene-expression microarray data. Bioinformatics 18 (Suppl 1), S105–S110.
20. Wold, H. (1966) Estimation of principal components and related models by iterative least squares, in (Krishnaiaah, P. R., Ed.), Multivariate Analysis, Academic, New York, NY, pp. 391–420.
21. Duda, R. O., et al. (2000) Pattern Classification, 2nd ed, Wiley, New York, NY, p. 680.
22. Kohonen, T. (1990) The self-organizing map. Proc IEEE 78, 1464.
23. Kohonen, T. (2001) Self-organizing maps, in (Huang, T. S., Kohonen, T., Schroeder, M. R., eds), Springer Series in Information Sciences, 3 ed, Springer, New York, NY, p. 501.
24. Wold, S., et al. (2001) PLS-regression: a basic tool of chemometrics. Chemom Intell Lab Syst 58, 109–130.
25. Höskuldsson, A. (1988) PLS regression methods. J Chemom 2, 211–228.
26. Trygg, J., et al. (2002) Orthogonal projections to latent structures (O-PLS). J Chemom 16, 119–128.
27. Wiklund, S. et al. (2007) Visualization of GC/TOF-MS-based metabolomics data for identification of biochemically interesting compounds using OPLS class models. Anal Chem 80, 115–122.
28. Mitchell, M. (1996) An Introduction to Genetic Algorithms, MIT Press, Cambridge, MA, p. 205.
29. Cavill, R., et al. (2009) Genetic algorithms for simultaneous variable and sample selection in metabonomics. Bioinformatics 25, 112–118.
30. Noda, I. (1990) 2-Dimensional infrared (2d ir) spectroscopy – theory and applications. Appl Spectrosc 44, 550–561.
31. 1 H NMR data sets. Anal Chem 77, 1282.
32. Couto Alves, A., et al. (2009) Analytic properties of statistical total correlation spectroscopy (STOCSY) based information recovery in 1 h NMR metabolic data sets. Anal Chem 81, 2075–2084.
33. Cloarec, O., et al. (2007) Virtual chromatographic resolution enhancement in cryoflow LC-NMR experiments via statistical total correlation spectroscopy. Anal Chem 79, 3304–3311.
34. Smith, L. M., et al. (2007) Statistical correlation and projection methods for improved information recovery from diffusion-edited NMR spectra of biological samples. Anal Chem 79, 5682–5689.
35. Coen, M., et al. (2007) Heteronuclear 1 h–31p statistical total correlation NMR spectroscopy of intact liver for metabolic biomarker assignment: application to galactosamine-induced hepatotoxicity. Anal Chem 79, 8956–8966.
36. Keun, H. C., et al. (2008) Heteronuclear 19f-1 h statistical total correlation spectroscopy as a tool in drug metabolism: study of flucloxacillin biotransformation. Anal Chem 80, 1073–1079.
37. Wang, Y., et al. (2008) Magic angle spinning NMR and 1 h–31p heteronuclear statistical total correlation spectroscopy of intact human gut biopsies. Anal Chem 80, 1058–1066.
38. Crockford, D. J., et al. (2006) Statistical heterospectroscopy, an approach to the integrated analysis of NMR and UPLC-MS data sets: application in metabonomic toxicology studies. Anal Chem 78, 363–371.
39. Robinette, S. L., et al. (2009) Cluster analysis statistical spectroscopy using nuclear magnetic resonance generated metabolic data sets from perturbed biological systems. Anal Chem 81, 6581–6589.