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Artificial Intelligence and Expert Systems in Mass Spectrometry

Mass Spectrometry

  1. Ronald C. Beavis1,
  2. Steven M. Colby2,
  3. Royston Goodacre3,
  4. Peter de B. Harrington4,
  5. James P. Reilly5,
  6. Stephen Sokolow6,
  7. Charles W. Wilkerson7

Published Online: 15 SEP 2006

DOI: 10.1002/9780470027318.a6002

Encyclopedia of Analytical Chemistry

Encyclopedia of Analytical Chemistry

How to Cite

Beavis, R. C., Colby, S. M., Goodacre, R., Harrington, P. d. B., Reilly, J. P., Sokolow, S. and Wilkerson, C. W. 2006. Artificial Intelligence and Expert Systems in Mass Spectrometry. Encyclopedia of Analytical Chemistry. .

Author Information

  1. 1

    Proteometrics LLC, New York, NY, USA

  2. 2

    Scientific Instrument Services, Inc., Ringoes, NJ, USA

  3. 3

    University of Wales, Aberystwyth, UK

  4. 4

    Ohio University, Athens, OH, USA

  5. 5

    Indiana University, Bloomington, IN, USA

  6. 6

    Bear Instruments, Santa Clara, CA, USA

  7. 7

    Los Alamos National Laboratory, Los Alamos, NM, USA

Publication History

  1. Published Online: 15 SEP 2006

Abstract

This article provides a brief introduction to aspects of mass spectrometry (MS) that employ artificial intelligence (AI) and expert system (ES) technology. These areas have grown rapidly with the development of computer software and hardware capabilities. In many cases, they have become fundamental parts of modern mass spectrometers.

Specific attention is paid to applications that demonstrate how important features of MS are now dependent on AI and ESs. The following topics are specifically covered: history, MS data systems, biological applications, artificial neural networks (ANNs), and optimization techniques.