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SELDI-TOF Mass Spectrometry Protein Data

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Bioinformatics and Computational Biology Solutions Using R and Bioconductor

Part of the book series: Statistics for Biology and Health ((SBH))

Abstract

The term proteome is used to denote the set of proteins encoded by a genome, and proteomics is the study of the expression and interactions of the proteins, which can depend on many factors such as cell type, treatment, tissue type, developmental state, and disease state. Conceptually, this is similar to the transcriptomics technologies discussed in Chapters 2-4; however, due to the more complicated chemistry of proteins, compared to RNA, the field has a different and diverse set of technologies and produces a wide range of specific challenges. Here we discuss one particular mass spectrometry technology.

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Authors
  1. X. Li
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  2. R. Gentleman
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  3. X. Lu
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  4. Q. Shi
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  5. J.D. Iglehart
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  6. L. Harris
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  7. A. Miron
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Editor information

Editors and Affiliations

  1. Program in Computational Biology Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N, M2-B876, PO Box 19024, Seattle, Washington, 98109-1024, USA

    Robert Gentleman

  2. Channing Laboratory Brigham and Women’s Hospital, Harvard Medical School, 181 Longwood Ave, Boston, MA, 02115, USA

    Vincent J. Carey

  3. European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, CB10 1SD, UK

    Wolfgang Huber

  4. Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD, 21205, USA

    Rafael A. Irizarry

  5. Division of Biostatistics School of Public Health, University of California Berkeley, 140 Earl Warren Hall, #7360, Berkeley, CA, 94720-7360, USA

    Sandrine Dudoit

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© 2005 Springer Science+Business Media, Inc.

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Li, X. et al. (2005). SELDI-TOF Mass Spectrometry Protein Data. In: Gentleman, R., Carey, V.J., Huber, W., Irizarry, R.A., Dudoit, S. (eds) Bioinformatics and Computational Biology Solutions Using R and Bioconductor. Statistics for Biology and Health. Springer, New York, NY. https://doi.org/10.1007/0-387-29362-0_6

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