A mass spectrum of the peptide mixture resulting from the digestion of a protein by an enzyme can provide a fingerprint of great specificity--so specific, in fact, that it is often possible to identify the protein from this information alone, without ambiguity. The general approach is to take a small sample of the protein of interest and digest it with a proteolytic enzyme, such as trypsin. The resulting digest mixture is analyzed by mass spectrometry, the ionization techniques of choice being matrix-assisted laser desorption or electrospray ionization. The experimental mass values are then compared with a database of peptide mass values, calculated by applying the enzyme cleavage rules to the entries in one of the major collections of sequence data, such as SwissProt or PIR. By using an appropriate scoring algorithm, the closest match or matches can be identified. If the "unknown" protein was present in the sequence database, then the goal is to identify that precise entry. If the sequence database does not contain the unknown protein, then a successful search will identify those entries that exhibit the closest sequence homology, often equivalent proteins from related species. An inverted strategy, in which experimental peptide mass fingerprints are accumulated in a database, has significant potential for identifying coding regions within sequence data from genomic DNA and, in doing so, correlating the genes with their expressed proteins. This review aims to provide an overview of the technique, compare the different database matching algorithms which have been described in the literature, and discuss the practical and theoretical factors which influence identification accuracy.