Probability Based Matching PBM

McLafferty and Stauffer published in The Wiley Registry of Mass Spectral Data a collection of about 380000 spectra of over 200000 compounds [3]. It is the largest and most comprehensive library of reference spectra that contains over 180000 searchable structures and over 2 million chemical names. The eighth edition of The Wiley Registry of Mass Spectral Data is available in electronic format and is compatible with the software of most instrument manufacturers and NIST MSSearch. Furthermore, it is accompanied by an interpretation help program called Probability Based Matching (PBM). 

Three different mass spectrometry search algorithms dominate the database searching systems commercially available today. The Cornell University Probability Based Matching (PBM) software, The Integrated Control System (INCOS) and the MassLib system (see below) with the SISCOM search software. 

F. E. McLafferty. This algorithm, called Probability Based Matching or PBM, employs a large number of fragment ions in a reverse search mode (4) to provide reliable identification and quantitation of an individual, specific compound even though the mass spectral measurements are derived from a mixture of two or more compounds (5). 

The most unique and valuable feature of Probability Based Matching, when applied to biological extracts, is its ability to automatically detect the existence of contaminations in a GC peak and to eliminate their interferences. This unusual feat can be accomplished because PBM is a "self-adapting" SIM technique i.e. the computer decides which ions in the contracted spectrum contain valid data and concurrently rejects ions that are contaminated due to the presence of impurities. 

A completely different search strategy forms the basis of the PBM algorithm (probability based match). The statistical mathematical treatment by Prof. McLafferty allows predictions to be made on the probable identity of a substance suggestion (Atwater et al, 1985 Palisade Corporation, 1994). The search procedure was developed in the 1970s at Cornell University as part of the Cornell algorithm (STIRS, the self-training interpretative and retrieval system as an interpretative system). In the subsequent years, parts of the PBM procedure... 

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