Literature DB >> 19176559

A novel comprehensive wave-form MS data processing method.

Shuo Chen1, Ming Li, Don Hong, Dean Billheimer, Huiming Li, Baogang J Xu, Yu Shyr.   

Abstract

MOTIVATION: Mass spectrometry (MS) can generate high-throughput protein profiles for biomedical research to discover biologically related protein patterns/biomarkers. The noisy functional MS data collected by current technologies, however, require consistent, sensitive and robust data-processing techniques for successful biomedical application. Therefore, it is important to detect features precisely for each spectrum, quantify them well and assign a unique label to features from the same protein/peptide across spectra.
RESULTS: In this article, we propose a new comprehensive MS data preprocessing package, Wave-spec, which includes several novel algorithms. It can overcome several conventional difficulties. Wave-spec can be applied to multiple types of MS data generated with different MS technologies. Results from this new package were evaluated and compared to several existing approaches based on a MALDI-TOF MS dataset. AVAILABILITY: An example of MATLAB scripts used to implement the methods described in this article, along with Supplementary Figures, can be found at http://www.vicc.org/biostatistics/supp.php. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Year:  2009        PMID: 19176559      PMCID: PMC2732299          DOI: 10.1093/bioinformatics/btp060

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  13 in total

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2.  Feature extraction and quantification for mass spectrometry in biomedical applications using the mean spectrum.

Authors:  Jeffrey S Morris; Kevin R Coombes; John Koomen; Keith A Baggerly; Ryuji Kobayashi
Journal:  Bioinformatics       Date:  2005-01-26       Impact factor: 6.937

3.  Protocols for disease classification from mass spectrometry data.

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4.  Determination of monoisotopic masses and ion populations for large biomolecules from resolved isotopic distributions.

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Journal:  J Am Soc Mass Spectrom       Date:  1995-04       Impact factor: 3.109

5.  Improved peak detection and quantification of mass spectrometry data acquired from surface-enhanced laser desorption and ionization by denoising spectra with the undecimated discrete wavelet transform.

Authors:  Kevin R Coombes; Spiridon Tsavachidis; Jeffrey S Morris; Keith A Baggerly; Mien-Chie Hung; Henry M Kuerer
Journal:  Proteomics       Date:  2005-11       Impact factor: 3.984

6.  Detection of pre-neoplastic and neoplastic prostate disease by MALDI profiling of urine.

Authors:  Amosy E M'Koma; David L Blum; Jeremy L Norris; Tatsuki Koyama; Dean Billheimer; Saundra Motley; Mayshan Ghiassi; Nika Ferdowsi; Indrani Bhowmick; Sam S Chang; Jay H Fowke; Richard M Caprioli; Neil A Bhowmick
Journal:  Biochem Biophys Res Commun       Date:  2006-12-22       Impact factor: 3.575

7.  Serum protein fingerprinting coupled with a pattern-matching algorithm distinguishes prostate cancer from benign prostate hyperplasia and healthy men.

Authors:  Bao-Ling Adam; Yinsheng Qu; John W Davis; Michael D Ward; Mary Ann Clements; Lisa H Cazares; O John Semmes; Paul F Schellhammer; Yutaka Yasui; Ziding Feng; George L Wright
Journal:  Cancer Res       Date:  2002-07-01       Impact factor: 12.701

8.  Mass spectrometry to classify non-small-cell lung cancer patients for clinical outcome after treatment with epidermal growth factor receptor tyrosine kinase inhibitors: a multicohort cross-institutional study.

Authors:  Fumiko Taguchi; Benjamin Solomon; Vanesa Gregorc; Heinrich Roder; Robert Gray; Kazuo Kasahara; Makoto Nishio; Julie Brahmer; Anna Spreafico; Vienna Ludovini; Pierre P Massion; Rafal Dziadziuszko; Joan Schiller; Julia Grigorieva; Maxim Tsypin; Stephen W Hunsucker; Richard Caprioli; Mark W Duncan; Fred R Hirsch; Paul A Bunn; David P Carbone
Journal:  J Natl Cancer Inst       Date:  2007-06-06       Impact factor: 13.506

9.  Proteomic patterns of tumour subsets in non-small-cell lung cancer.

Authors:  Kiyoshi Yanagisawa; Yu Shyr; Baogang J Xu; Pierre P Massion; Paul H Larsen; Bill C White; John R Roberts; Mary Edgerton; Adriana Gonzalez; Sorena Nadaf; Jason H Moore; Richard M Caprioli; David P Carbone
Journal:  Lancet       Date:  2003-08-09       Impact factor: 79.321

10.  An Automated Peak Identification/Calibration Procedure for High-Dimensional Protein Measures From Mass Spectrometers.

Authors:  Yutaka Yasui; Dale McLerran; Bao-Ling Adam; Marcy Winget; Mark Thornquist; Ziding Feng
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  5 in total

1.  Wave-spec: a preprocessing package for mass spectrometry data.

Authors:  Ming Li; Shuo Chen; Joan Zhang; Heidi Chen; Yu Shyr
Journal:  Bioinformatics       Date:  2011-01-05       Impact factor: 6.937

Review 2.  Image analysis tools and emerging algorithms for expression proteomics.

Authors:  Andrew W Dowsey; Jane A English; Frederique Lisacek; Jeffrey S Morris; Guang-Zhong Yang; Michael J Dunn
Journal:  Proteomics       Date:  2010-12       Impact factor: 3.984

3.  Lung cancer diagnosis from proteomic analysis of preinvasive lesions.

Authors:  S M Jamshedur Rahman; Adriana L Gonzalez; Ming Li; Erin H Seeley; Lisa J Zimmerman; Xueqiong J Zhang; M Lisa Manier; Sandra J Olson; Ronak N Shah; Alison N Miller; Joe B Putnam; York E Miller; Wilbur A Franklin; William J Blot; David P Carbone; Yu Shyr; Richard M Caprioli; Pierre P Massion
Journal:  Cancer Res       Date:  2011-04-12       Impact factor: 12.701

4.  Joint Bounding of Peaks Across Samples Improves Differential Analysis in Mass Spectrometry-Based Metabolomics.

Authors:  Leslie Myint; Andre Kleensang; Liang Zhao; Thomas Hartung; Kasper D Hansen
Journal:  Anal Chem       Date:  2017-03-07       Impact factor: 6.986

5.  Differential intrahepatic phospholipid zonation in simple steatosis and nonalcoholic steatohepatitis.

Authors:  Julia Wattacheril; Erin H Seeley; Peggi Angel; Heidi Chen; Benjamin P Bowen; Christian Lanciault; Richard M Caprioli; Naji Abumrad; Charles Robb Flynn
Journal:  PLoS One       Date:  2013-02-25       Impact factor: 3.240

  5 in total

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