The review provides a brief overview of techniques used for interpretation of mass spectrometric data acquired in proteomic experiments. Processing of the data by bioinformatics is an important part of protein identification in proteomics. Analyzed samples can be measured using different mass spectrometric techniques and the obtained data require different methods of processing. Genomic databases rapidly grow and a suitable way of manipulation with data becomes a crucial step for their correct interpretation. Basic methods of interpretation of mass spectrometric data are summarized and some examples show how the corresponding programs work.