EURASIP Journal on Applied Signal Processing 
Volume 2006 (2006), Article ID 63582, 9 pages
doi:10.1155/ASP/2006/63582

MALDI-TOF Baseline Drift Removal Using Stochastic Bernstein Approximation

Joseph Kolibal1 and Daniel Howard2

 1Department of Mathematics, College of Science & Technology, The University of Southern Mississippi, Hattiesburg 39406-0001, MS, USA
2QinetiQ PLC, Malvern WR14 3PS, Worcestershire, United Kingdom
Received 7 July 2005; Revised 21 August 2005; Accepted 1 December 2005

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 σ(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 σ) or tuned with evolutionary computation (for σ(x)).