Application of wavelet transform to the MS-based proteomics data preprocessing

Published

Conference Paper

Mass Spectrometry (MS) has become one of the major detection technologies for high-throughput proteomics. The preprocessing of mass spectra is crucial for its subsequent analysis like biomarker discovery or protein identification. Wavelet transform is gradually becoming an important methodology in the MS data preprocessing. This paper reviews the application of wavelet transforms in quality control, smoothing and peak detection of MS data preprocessing. It also proposes an improved Discrete Wavelet Transform (DWT) smoothing algorithm, which utilizes the cross-level DWT coefficients information during smoothing. Most of the algorithms described in this paper are included or will be included in the Bioconductor MassSpecWavelet package. ©2007 IEEE.

Full Text

Duke Authors

Cited Authors

  • Du, P; Lin, SM; Kibbe, WA; Wang, H

Published Date

  • December 1, 2007

Published In

  • Proceedings of the 7th Ieee International Conference on Bioinformatics and Bioengineering, Bibe

Start / End Page

  • 680 - 686

International Standard Book Number 10 (ISBN-10)

  • 1424415098

International Standard Book Number 13 (ISBN-13)

  • 9781424415090

Digital Object Identifier (DOI)

  • 10.1109/BIBE.2007.4375634

Citation Source

  • Scopus