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

Pan Du; Simon M. Lin; Warren A. Kibbe; Haihui Wang

doi:10.1109/BIBE.2007.4375634

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

Pan Du^*
, Simon M. Lin
, Warren A. Kibbe
, Haihui Wang

^*Corresponding author for this work

School of Mathematical Sciences

Northwestern University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Scopus citations

Abstract

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.

Original language	English
Title of host publication	Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
Pages	680-686
Number of pages	7
DOIs	https://doi.org/10.1109/BIBE.2007.4375634
State	Published - 2007
Event	7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE - Boston, MA, United States Duration: 14 Jan 2007 → 17 Jan 2007

Publication series

Name	Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

Conference

Conference	7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
Country/Territory	United States
City	Boston, MA
Period	14/01/07 → 17/01/07

Keywords

Bioconductor
Mass spectrum
Preprocessing
Proteomics
Smoothing
Wavelet transform

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10.1109/BIBE.2007.4375634

Cite this

Du, P., Lin, S. M., Kibbe, W. A., & Wang, H. (2007). Application of wavelet transform to the MS-based proteomics data preprocessing. In Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE (pp. 680-686). Article 4375634 (Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE). https://doi.org/10.1109/BIBE.2007.4375634

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title = "Application of wavelet transform to the MS-based proteomics data preprocessing",

abstract = "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.",

keywords = "Bioconductor, Mass spectrum, Preprocessing, Proteomics, Smoothing, Wavelet transform",

author = "Pan Du and Lin, \{Simon M.\} and Kibbe, \{Warren A.\} and Haihui Wang",

year = "2007",

doi = "10.1109/BIBE.2007.4375634",

language = "英语",

isbn = "1424415098",

series = "Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE",

pages = "680--686",

booktitle = "Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE",

note = "7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE ; Conference date: 14-01-2007 Through 17-01-2007",

}

Du, P, Lin, SM, Kibbe, WA & Wang, H 2007, Application of wavelet transform to the MS-based proteomics data preprocessing. in Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE., 4375634, Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE, pp. 680-686, 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE, Boston, MA, United States, 14/01/07. https://doi.org/10.1109/BIBE.2007.4375634

Application of wavelet transform to the MS-based proteomics data preprocessing. / Du, Pan; Lin, Simon M.; Kibbe, Warren A. et al.
Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE. 2007. p. 680-686 4375634 (Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Lin, Simon M.

AU - Kibbe, Warren A.

AU - Wang, Haihui

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N2 - 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.

AB - 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.

KW - Bioconductor

KW - Mass spectrum

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KW - Proteomics

KW - Smoothing

KW - Wavelet transform

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M3 - 会议稿件

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T3 - Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

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BT - Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

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Y2 - 14 January 2007 through 17 January 2007

ER -

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

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