Recent developments in proteomics and genomics provide huge quantities of data to analyze. Automatic interpretation of mass spectrometry data has become essential for high-throughput processes aiming to study complete proteomes. There exist two main sources of mass spectrometric data: peptide mass fingerprint and fragmentation spectra, both of which require specific bioinformatic algorithms. We present a survey of these algorithms and discuss the efficiency of the different approaches and the possible improvements that may lead to a complete automatic high-throughput identification process.