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MICE: Multiple-Peak Identification, Characterization, and Estimation

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MICE—multiple-peak identification, characterization, and estimation—is a procedure for estimating a lower bound of the number of frequency peaks and for estimating the frequency peak parameters. The leading application is protein structure determination using nuclear magnetic resonance (NMR) experiments. NMR frequency data are multiple-peak data, where each frequency peak corresponds to two connected atoms in the three-dimensional protein structure. We analyze the NMR frequency data through a series of steps: a preliminary step for separating the signal from the background followed by identification of local maxima up to a noise-level-dependent threshold, estimation of the frequency peak parameters using an iterative algorithm, and detection of mixtures of peaks using hypothesis testing.

Keywords: Backfitting; Mixture detection; Nuclear magnetic resonance; Protein structure determination; Tensor-product wavelet decomposition

Document Type: Research Article


Affiliations: Industrial Systems and Engineering School, Georgia Institute of Technology, Atlanta, Georgia 30313, U.S.A., Email:

Publication date: June 1, 2007


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