Kernel-PCA denoising of artifact-free protein NMR spectra

Author

Stadlthanner, K. ; Lang, E.W. ; Gruber, P. ; Theis, F.J. ; Tomé, A.M. ; Teixeira, A.R. ; Puntonet, C.G.

Author_Institution

Inst. of Biophys., Univ. of Regensburg, Regensburg, Germany

Volume

3

fYear

2004

fDate

25-29 July 2004

Firstpage

1959

Abstract

Multidimensional ¹H NMR spectra of biomolecules dissolved in light water are contaminated by an intense water artifact. Generalized eigenvalue decomposition methods using congruent matrix pencils are used to separate the water artefact from the protein spectra. Due to the statistical separation process, however, noise is introduced into the reconstructed spectra. Hence Kernel-based denoising techniques are discussed to obtain noise- and artifact-free 2D NOESY NMR spectra of proteins.

Keywords

biological NMR; eigenvalues and eigenfunctions; macromolecules; matrix decomposition; molecular biophysics; principal component analysis; proteins; signal denoising; artifact free 2D NOESY NMR spectra; artifact free protein NMR spectra; biomolecules; congruent matrix pencils; generalized eigenvalue decomposition; intense water artifact; kernel PCA denoising; kernel based denoising; multidimensional NMR spectra; noise free 2D NOESY NMR spectra; statistical separation process; Eigenvalues and eigenfunctions; Kernel; Matrix decomposition; Noise reduction; Nuclear magnetic resonance; Principal component analysis; Proteins; Signal processing; Water pollution; Water resources;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on

ISSN

1098-7576

Print_ISBN

0-7803-8359-1

Type

conf

DOI

10.1109/IJCNN.2004.1380913

Filename

1380913