TY  - JOUR
A1  - Tikole, Suhas
A1  - Jaravine, Victor
A1  - Rogov, Vladimir V.
A1  - Dötsch, Volker
A1  - Güntert, Peter
T1  - Peak picking NMR spectral data using non-negative matrix factorization
T2  - BMC bioinformatics
N2  - Background: Simple peak-picking algorithms, such as those based on lineshape fitting, perform well when peaks are completely resolved in multidimensional NMR spectra, but often produce wrong intensities and frequencies for overlapping peak clusters. For example, NOESY-type spectra have considerable overlaps leading to significant peak-picking intensity errors, which can result in erroneous structural restraints. Precise frequencies are critical for unambiguous resonance assignments.
Results: To alleviate this problem, a more sophisticated peaks decomposition algorithm, based on non-negative matrix factorization (NMF), was developed. We produce peak shapes from Fourier-transformed NMR spectra. Apart from its main goal of deriving components from spectra and producing peak lists automatically, the NMF approach can also be applied if the positions of some peaks are known a priori, e.g. from consistently referenced spectral dimensions of other experiments.
Conclusions: Application of the NMF algorithm to a three-dimensional peak list of the 23 kDa bi-domain section of the RcsD protein (RcsD-ABL-HPt, residues 688-890) as well as to synthetic HSQC data shows that peaks can be picked accurately also in spectral regions with strong overlap.
KW  - Non-negative matrix factorization
KW  - Peak picking
KW  - NMR spectrum
KW  - Peak overlap
Y1  - 2014
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/33032
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-330323
SN  - 1471-2105
N1  - © 2014 Tikole et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
VL  - 15
IS  - 46
PB  - BioMed Central
CY  - London
ER  -