Computer-assisted interpretation of mass spectra

Under Defense Advanced Research Projects Agency sponsorship, APL is develop ing a miniature time-of-flight (TOF) mass spectrometer for early warning ag ainst exposure to chemical/biological agents, Intended for operation by a w ide range of military and civilian personnel, the instrument must be able t o detect and identify pathological agents wit-hin minutes. Key to this miss ion is the spectrometer operator's interpretation of the data. Typically, i nterpretation of mass spectra has been the realm of professional chemists a nd 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, signature s. For precisely known signatures, a vector space problem can be formulated to estimate the optimum approximation of the measured spectrum with a comb ination of stored library signatures of threat agents. Fdr partially unknow n signatures, a Bayesian probabilistic approach has been taken to relate th e potentially variable signature of a bacterial threat to likelihoods of ch emical composition of bacterial lipids.