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Identifies peptides from a sequence database with tandem mass spectrometry data. PEAKS employs de novo sequencing as a subroutine and exploits the de novo sequencing results to improve both the speed and accuracy of the database search. Each protein obtains a score by adding its three highest peptide CAA scores, and the protein feature of a peptide is the maximum score of the proteins containing this peptide. PEAKS also provides a user-friendly interface to show each resultant peptide spectrum match from de novo sequencing.


An open-source software that leverages inferred sequence tags to identify unanticipated mutations from clinical proteomic data sets. TagRecon can effectively identify peptides even in the face of errors in their corresponding FASTA entries. The software outperformed other published algorithms in identifying mutant peptides from cancer samples. TagRecon is incorporated into a computational pipeline built for high-throughput environments. Analysis of colon cancer data sets with TagRecon revealed modifications associated with extracellular matrix degradation.