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Book Chapter: Peak Detection with Chemical Noise Removal Using Short-Time FFT for a Kind of MALDI Data

TitlePeak Detection with Chemical Noise Removal Using Short-Time FFT for a Kind of MALDI Data
Authors
KeywordsPeak detection
adaptive short time discrete Fourier transform
undecimated wavelet transforml
Issue Date2007
PublisherWorld Publishing Corporation.
Citation
Peak Detection with Chemical Noise Removal Using Short-Time FFT for a Kind of MALDI Data. In Zhang, XS, Chen, L and Yu, LY et al. (Eds.). Optimization and Systems Biology, 222-231. Beijing: World Publishing Corporation, 2007 How to Cite?
AbstractPeak detection is the first step in biomarker extraction from the mass spectrometry data, which significantly influences the results of the following steps. Designing a good method for peak detection greatly depends on the properties of the data. In this paper, we propose a novel automatic peak detection method without the a priori knowledge on the mass of the proteins for a kind of MALDI data, which have a regular noise pattern called chemical noise except the random noise. The random noise is removed by using the undecimated wavelet transform. An adaptive short time discrete Fourier transform is proposed to do the chemical noise de-noising. We combine the possible peaks corresponding to one protein by extracting an envelope over them. Depending on the signal-to-noise ratio, the desired peaks that have the highest intensity among their peak clusters in each individual spectrum are detected. We examine the performance of the method in the carotid artery disease data set that shows the efficiency of the method. With the chemical noise removal, the signal-to-noise ratio of the peaks is increased greatly compared to the result without chemical noise removal.
DescriptionThe First International Symposium, OSB'07, Beijing, China, August 8-10, 2007, Proceedings
Persistent Identifierhttp://hdl.handle.net/10722/119222
ISBN
Series/Report no.Lecture Notes in Operations Research, v. 7

 

DC FieldValueLanguage
dc.contributor.authorZhang, Sen_HK
dc.contributor.authorZhou, Xen_HK
dc.contributor.authorWang, Hen_HK
dc.contributor.authorSuffredini, Aen_HK
dc.contributor.authorGonzales, Den_HK
dc.contributor.authorChing, WKen_HK
dc.contributor.authorNg, KPen_HK
dc.contributor.authorWong, STCen_HK
dc.date.accessioned2010-09-26T08:41:35Z-
dc.date.available2010-09-26T08:41:35Z-
dc.date.issued2007en_HK
dc.identifier.citationPeak Detection with Chemical Noise Removal Using Short-Time FFT for a Kind of MALDI Data. In Zhang, XS, Chen, L and Yu, LY et al. (Eds.). Optimization and Systems Biology, 222-231. Beijing: World Publishing Corporation, 2007-
dc.identifier.isbn978-7-5062-7292-6/O568-
dc.identifier.urihttp://hdl.handle.net/10722/119222-
dc.descriptionThe First International Symposium, OSB'07, Beijing, China, August 8-10, 2007, Proceedings-
dc.description.abstractPeak detection is the first step in biomarker extraction from the mass spectrometry data, which significantly influences the results of the following steps. Designing a good method for peak detection greatly depends on the properties of the data. In this paper, we propose a novel automatic peak detection method without the a priori knowledge on the mass of the proteins for a kind of MALDI data, which have a regular noise pattern called chemical noise except the random noise. The random noise is removed by using the undecimated wavelet transform. An adaptive short time discrete Fourier transform is proposed to do the chemical noise de-noising. We combine the possible peaks corresponding to one protein by extracting an envelope over them. Depending on the signal-to-noise ratio, the desired peaks that have the highest intensity among their peak clusters in each individual spectrum are detected. We examine the performance of the method in the carotid artery disease data set that shows the efficiency of the method. With the chemical noise removal, the signal-to-noise ratio of the peaks is increased greatly compared to the result without chemical noise removal.-
dc.languageengen_HK
dc.publisherWorld Publishing Corporation.-
dc.relation.ispartofOptimization and Systems Biology-
dc.relation.ispartofseriesLecture Notes in Operations Research, v. 7-
dc.subjectPeak detection-
dc.subjectadaptive short time discrete Fourier transform-
dc.subjectundecimated wavelet transforml-
dc.titlePeak Detection with Chemical Noise Removal Using Short-Time FFT for a Kind of MALDI Dataen_HK
dc.typeBook_Chapteren_HK
dc.identifier.emailChing, WK: wching@HKUCC.hku.hken_HK
dc.identifier.emailNg, KP: kkpong@hkusua.hku.hken_HK
dc.identifier.authorityChing, WK=rp00679en_HK
dc.description.naturelink_to_OA_fulltext-
dc.identifier.hkuros132578en_HK
dc.identifier.volume7en_HK
dc.identifier.spage222en_HK
dc.identifier.epage231en_HK

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