Document Type

Article

Publication Date

2006

Department

Mathematics

School

Mathematics and Natural Sciences

Abstract

Stochastic Bernstein (SB) approximation can tackle the problem of baseline drift correction of instrumentation data. This is demonstrated for spectral data: matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF) data. Two SB schemes for removing the baseline drift are presented: iterative and direct. Following an explanation of the origin of the MALDI-TOF baseline drift that sheds light on the inherent difficulty of its removal by chemical means, SB baseline drift removal is illustrated for both proteomics and genomics MALDI-TOF data sets. SB is an elegant signal processing method to obtain a numerically straightforward baseline shift removal method as it includes a free parameter sigma(x) that can be optimized for different baseline drift removal applications. Therefore, research that determines putative biomarkers from the spectral data might benefit from a sensitivity analysis to the underlying spectral measurement that is made possible by varying the SB free parameter. This can be manually tuned ( for constant sigma) or tuned with evolutionary computation ( for sigma( x)). Copyright (C) 2006 Hindawi Publishing Corporation. All rights reserved.

Comments

Published by EURASIP Journal on Advances in Signal Processing at 10.1155/asp/2006/63582.

Publication Title

Eurasip Journal On Applied Signal Processing

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