Towards fast and reliable candidate peptide indexing for Tandem Mass Spectrometry data

Many algorithms for protein and peptide identification from Tandem Mass Spectrometry (MS/MS) data have been published. The majority of such methods are based on sequence or spectral database search: experimental spectra are matched to theoretical spectra characterizing known peptide sequences. Hits define candidate peptides. In this context, the development of reliable candidate peptide indexing and ranking techniques for accelerated pre-processing of large datasets still remains a challenge.