A Bayesian approach for the alignment of high-resolution NMR spectra

Seoung Bum Kim, Zhou Wang, Basavaraj Hiremath

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


Metabolic analysis with high-resolution nuclear magnetic resonance (NMR) enables simultaneous investigation of numerous chemical species in response to biochemical changes in subjects. When the analysis involves comparing two or more NMR spectra, it is essential to properly align them because small variations across different spectra influence the alignment and thus, interfere with direct comparisons between samples. We propose a new alignment method within the Bayesian modeling framework. The proposed method allows us to estimate the amplitude and phase shifts simultaneously and to obtain robust results in the existence of noise. Effectiveness of our proposed method is demonstrated through real NMR spectra in human plasma and a comparison study with dynamic time warping and correlated optimized warping, two widely used alignment methods in spectral data.

Original languageEnglish
Pages (from-to)19-32
Number of pages14
JournalAnnals of Operations Research
Issue number1
Publication statusPublished - 2010 Feb
Externally publishedYes


  • Alignment
  • Amplitude (baseline intensity) variation
  • Bayesian method
  • Nuclear magnetic resonance (NMR)
  • Phase (spectral) shift

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Management Science and Operations Research


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