Computer-assisted interpretation of mass spectra

Carleton S. Hayek, Fernando J Pineda, Otis W. Doss, Jeffrey S. Lin

Research output: Contribution to journalArticle

Abstract

Under Defense Advanced Research Projects Agency sponsorship, APL is developing a miniature time-of-flight (TOF) mass spectrometer for early warning against exposure to chemical/biological agents. Intended for operation by a wide range of military and civilian personnel, the instrument must be able to detect and identify pathological agents within minutes. Key to this mission is the spectrometer operator's interpretation of the data. Typically, interpretation of mass spectra has been the realm of professional chemists and biochemists. Other operators must rely on computer classification of the TOF mass spectrometer's output. We describe algorithms that can be used to interpret mass spectra and that have been successful on a limited data set. These algorithms handle precisely known, and partially unknown, signatures. For precisely known signatures, a vector space problem can be formulated to estimate the optimum approximation of the measured spectrum with a combination of stored library signatures of threat agents. For partially unknown signatures, a Bayesian probabilistic approach has been taken to relate the potentially variable signature of a bacterial threat to likelihoods of chemical composition of bacterial lipids.

Original languageEnglish (US)
Pages (from-to)363-370
Number of pages8
JournalJohns Hopkins APL Technical Digest (Applied Physics Laboratory)
Volume20
Issue number3
Publication statusPublished - 1999
Externally publishedYes

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Keywords

  • Computer classification
  • MALDI
  • Mass spectrum

ASJC Scopus subject areas

  • General
  • Physics and Astronomy (miscellaneous)

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