Mass Spectrometry Bioinformatics: Tools for Navigating the Proteomics Landscape

Central to the successful implementation of a proteomics pipeline are appropriate bioinformatics tools to provide a level of automation and standardization to the qualitative identification of proteins, quantitation of protein changes, data capture and storage, and integration with other data platforms. Many of these efforts are in various stages of maturity; however, the identification, or recognition, of peptides/proteins from mass spectrometry data, arguably the most developed area, continues to remain challenging due to the ever increasing size of proteomic datasets. Confident peptide and protein identification, including assignment of any post-translational modifications, is a necessary prerequisite for any proteomic study aimed at elucidating biological and physiological responses. This review includes discussions of bioinformatic approaches for the qualitative identification of peptides/proteins from mass spectrometry data as well as the software tools and the analytical considerations required for analysis. Issues related to placing a proteomics dataset in a larger biological context which includes splice variants, variations in databases, and neglected proteomes are also discussed.