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We describe the protein search engine "ProFound", which employs a Bayesian algorithm to identify proteins from protein databases using mass spectrometric peptide mapping data. The algorithm ranks protein candidates by taking into account individual properties of each protein in the database as well as other information relevant to the peptide mapping experiment. The program consistently identifies the correct protein(s) even when the data quality is relatively low or when the sample consists of a simple mixture of proteins. Illustrative examples of protein identifications are provided.
Zhang et al. (2000) studied this question.
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