Database searching is the major peptide identification method in shotgun proteomics. It searches tandem mass spectrometry (MS/MS) spectra against a protein database to identify target peptides. The success of such a database searching method relies on a scoring algorithm that can evaluate the quality of peptide-spectrum matches (PSMs) accurately. However, current scoring algorithms frequently generate inaccurate assignments due to variations and noises in the MS/MS spectra. To address this issue, we like to improve peptide identification by using additional information from other data sources.