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MICE: Multiple‐Peak Identification, Characterization, and Estimation
Author(s) -
Serban Nicoleta
Publication year - 2007
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.1541-0420.2006.00688.x
Subject(s) - identification (biology) , estimation , computer science , characterization (materials science) , statistics , computational biology , mathematics , biology , engineering , materials science , botany , systems engineering , nanotechnology
Summary 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.