Amino acid mutations in proteins can be found by searching tandem mass spectra acquired in shotgun proteomics experiments against protein sequences predicted from genomes. Traditionally, unconstrained searches for amino acid mutations have been accomplished by using a sequence tagging approach that combines de novo sequencing with database searching.
Allows a similarity search between de novo sequence tags and a database of proteins. SPIDER is an algorithm that focuses on the highlight of peptide mutations. It exploits it, coupled to the investigation of de novo sequencing errors, to explain the differences between the submitted sequence and the one which is stored in the database. This software can be used in conjunction with other products from the Bioinformatics Solutions company in order to detect homologous proteins.
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.
A database-searching algorithm for peptide and protein identification in shotgun proteomics. Hybrid Message Passing Interface/OpenMP parallelism of the new Sipros architecture allowed its computation to be scalable from desktops to supercomputers.
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.
Performs comprehensive in silico analyses. LeTE-fusion gives an ideal estimation of peptide and variant peptide detections. It derives a realistic estimation of the percentage of detectable genome-annotated variants in shotgun mass spectrometry (MS) experiments using peptides with experimental evidence. This tool is useful for the assessment of feasibility of detecting other types of peptides or variations.