A generally applicable method for the automated classification of 2D NMR peaks has been developed, based on a Bayesian approach coupled to a multivariate linear discriminant analysis of the data. The method can separate true NMR signals from noise signals, solvent stripes and artefact signals. The analysis relies on the assumption that the different signal classes have different distributions of specific properties such as line shapes, line widths and intensities. As to be expected, the correlation network of the distributions of the selected properties affects the choice of the discriminant function and the final selection of signal properties. The classification rule for the signal classes was deduced from Bayes's theorem. The method was successfully tested on a NOESY spectrum of HPr protein from Staphylococcus aureus. The calculated probabilities for the different signal class memberships are realistic and reliable, with a high efficiency of discrimination between peaks that are true NOE signals and those that are not.
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Borgias, J.W. and James, T.L. (1984) J. Magn. Reson., 59, 493–512.
Bretthorst, G.L., Hung, C.-C., D'Avignon, D.A. and Ackerman, J.J.H. (1988) J. Magn. Reson., 79, 369–376.
Brünger, A.T. (1993) X-PLOR Manual, Version 3.01, Yale University, New Haven, CT.
Cornfield, J. (1967) Rev. Int. Statist. Inst., 35, 34–49.
Cornfield, J. (1969) Biometrics, 25, 643–657.
Dietrich, W., Rüdel, C.H. and Neumann, M. (1991) J. Magn. Reson., 91, 1–11.
Ernst, R.R., Bodenhausen, G. and Wokaun, A. (1986) Principles of Nuclear Magnetic Resonance in One and Two Dimensions, Oxford Science Publication, Oxford.
Fesik, S.W. (1991) J. Med. Chem., 34, 2937–2945.
Fisher, R.A. (1936) Ann. Eugenics, 7, 179–188.
Garett, D.S., Powers, R., Gronenborn, A.M. and Clore, G.M. (1991) J. Magn. Reson., 95, 214–220.
Glaser, S. and Kalbitzer, H.R. (1987) J. Magn. Reson., 74, 450–463.
Griffey, R.H. and Redfield, A.G. (1987) Q. Rev. Biophys., 19, 51–82.
Güntert, P. and Wüthrich, K. (1992) J. Magn. Reson., 96, 403–407.
Hausser, K.H. and Kalbitzer, H.R. (1991) In NMR in Medicine and Biology: Structure Determination, Tomography, In Vivo Spectroscopy, Springer, Heidelberg, pp. 39–77.
Hoeffding, W. (1948) Ann. Math. Statist., 19, 546–557.
Hollander, M. and Wolfe, D.A. (1973) In Nonparametric Statistical Methods (Eds, Bradley, R., Hunter, H.S., Kendall, D.G. and Watson, G.S.) Wiley, New York, NY, pp. 228–236.
Jaynes, E.T. (1985) In Maximum-Entropy and Bayesian Methods in Inverse Problems (Eds, Smith, C.R. and Grandy, W.T.) Reidel, Dordrecht, pp. 21–58.
Jeener, J., Meier, B.H., Bachmann, P. and Ernst, R.R. (1979) J. Chem. Phys., 71, 4546–4553.
Kalbitzer, H.R., Hengstenberg, W., Rösch, P., Muss, P., Bernsmann, P., Dörschug, M. and Deutscher, J. (1982) Biochemistry, 21, 2879–2885.
Kalbitzer, H.R. and Hengstenberg, W. (1992) Eur. J. Biochem., 216, 205–214.
Keeper, J.W. and James, T.L. (1984) J. Magn. Reson., 57, 404–426.
Kleywegt, G.J., Lamerichs, R.M.J.N., Boelens, R. and Kaptein, R. (1989) J. Magn. Reson., 85, 186–197.
Kleywegt, G.J., Boelens, R. and Kaptein, R. (1990) J. Magn. Reson., 88, 601–608.
Manorelas, N. and Norton, R.S. (1992) J. Biomol. NMR, 2, 485–494.
Marion, D. and Wüthrich, K. (1983) Biochem. Biophys. Res. Commun., 113, 967–974.
Mehlkopf, A.F., Korbee, D. and Tiggelman, T.A. (1984) J. Magn. Reson., 58, 315–323.
Neidig, K.-P., Bodenmueller, H. and Kalbitzer, H.R. (1984) Biochem. Biophys. Res. Commun., 125, 1143–1150.
Neidig, K.-P. and Kalbitzer, H.R. (1990) J. Magn. Reson., 88, 155–160.
Neidig, K.-P. (1993) AURELIA User's Guide, Version 931101, Bruker Analytische Messtechnik, Rheinstetten.
Rouh, A., Louis-Joseph, A. and Lallemand, J.-Y. (1994) J. Biomol. NMR, 4, 505–518.
Saffrich, R., Beneicke, W., Neidig, K.-P. and Kalbitzer, H.R. (1992) J. Magn. Reson. Ser. B, 101, 304–308.
SAS (1985) SAS User's Guide: Basics, Version 5, SAS Institute Inc., Cary, NC.
Skilling, J. and Gull, S.F. (1985) In Maximum-Entropy and Bayesian Methods in Inverse Problems (Eds, Smith, C.R. and Grandy, W.T.) Reidel, Dordrecht, pp. 83–132.
Spearman, C. (1904) Am. J. Psychol., 15, 72–101.
Spearman, C. (1908) Br. J. Psychol. 2, 227–242.
Stoven, V., Mikou, A., Piveteau, D., Guittet, E. and Lallemand, J.-Y. (1989) J. Magn. Reson., 82, 163–168.
Tatsuoka, M.M. (1970) Multivariate Analysis Techniques for Educational and Psychological Research, Wiley, New York, NY, pp. 94–190.
Wiesböck, K. (1987) Ph.D. Thesis, University of Passau, Passau.
Wüthrich, K. (1986) NMR of Proteins and Nucleid Acids, Wiley, New York, NY.
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Antz, C., Neidig, K. & Kalbitzer, H.R. A general Bayesian method for an automated signal class recognition in 2D NMR spectra combined with a multivariate discriminant analysis. J Biomol NMR 5, 287–296 (1995). https://doi.org/10.1007/BF00211755
- Multivariate discriminant analysis
- 2D NMR spectroscopy
- Bayesian analysis
- Peak recognition
- NMR molecular structure