Using GFS to identify encoding genomic loci from protein mass spectral data.

Genome-based peptide fingerprint scanning (GFS) directly maps several types of protein mass spectral (MS) data to the loci in the genome that may have encoded for the protein. This process can be used either for protein identification or for proteogenomic mapping, which is gene-finding and annotation based on proteomic data. Inputs to the program are one or more mass spectrometry files from peptide mass fingerprinting and/or tandem MS (MS/MS) along with one or more sequences to search them against, and the output is the coordinates of any matches found.

GFSWeb: a web tool for genome-based identification of proteins from mass spectrometric samples.

The interpretation of mass spectrometry data for protein identification has become a vital component of proteomics research. However, since most existing software tools rely on protein databases, their success is limited, especially as the pace of annotation efforts fails to keep pace with sequencing. We present a publicly available, web-based version of a software tool that maps peptide mass fingerprint data directly to their genomic origin, allowing for genome-based, annotation-independent protein identification.

Prediction of posttranslational modifications using intact-protein mass spectrometric data.

We present a Web-based application that uses whole-protein masses determined by mass spectrometry to identify putative co- and posttranslational proteolytic cleavages and chemical modifications. The protein cleavage and modification engine (PROCLAME) requires as input an intact mass measurement and a precursor identification based on peptide mass fingerprinting or tandem mass spectrometry. This approach predicts mass-modifying events using a depth-first tree search, bounded by a set of rules controlled by a custom-built fuzzy logic engine, to explore a large number of possible combinations of modifications accounting for the experimental mass.