Time-domain signal modelling in multidimensional NMR experiments for estimation of relaxation parameters.
Yevgen MatviychukMark J BostockDaniel NietlispachDaniel J HollandPublished in: Journal of biomolecular NMR (2019)
We present a model-based method for estimation of relaxation parameters from time-domain NMR data specifically suitable for processing data in popular 2D phase-sensitive experiments. Our model is formulated in terms of commutative bicomplex algebra, which allows us to use the complete information available in an NMR signal acquired with principles of quadrature detection without disregarding any of its dimensions. Compared to the traditional intensity-analysis method, our model-based approach offers an important advantage for the analysis of overlapping peaks and is robust over a wide range of signal-to-noise ratios. We assess its performance with simulated experiments and then apply it for determination of [Formula: see text], [Formula: see text], and [Formula: see text] relaxation rates in datasets of a protein with more than 100 cross peaks.
Keyphrases
- magnetic resonance
- high resolution
- solid state
- smoking cessation
- human milk
- single molecule
- electronic health record
- big data
- air pollution
- high intensity
- data analysis
- healthcare
- health information
- solid phase extraction
- binding protein
- loop mediated isothermal amplification
- quantum dots
- preterm birth
- simultaneous determination