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MALDI-TOF Baseline Drift Removal Using Stochastic Bernstein Approximation

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 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) or tuned with evolutionary computation (for).

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Correspondence to Joseph Kolibal.

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Kolibal, J., Howard, D. MALDI-TOF Baseline Drift Removal Using Stochastic Bernstein Approximation. EURASIP J. Adv. Signal Process. 2006, 063582 (2006). https://doi.org/10.1155/ASP/2006/63582

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Keywords

  • Spectral Data
  • Free Parameter
  • Spectral Measurement
  • Evolutionary Computation
  • Inherent Difficulty