The application provides a bidirectional
peptide sequencing method based on a self-attention mechanism and application, and comprises the following steps: obtaining
mass spectrum
raw data,
processing the
mass spectrum
raw data to obtain
peptide features and secondary fragment
ion spectra associated with the
peptide features; inputting the peptide features and the secondary fragment
ion spectra into a bidirectional independent sequencing model in a bidirectional
peptide sequencing model to output bidirectional independent predicted candidate sequences, inputting the peptide features and the secondary fragment
ion spectra into a bidirectional interaction sequencing model in the bidirectional
peptide sequencing model to output bidirectional interaction predicted candidate sequences, and taking a union of the bidirectional independent predicted candidate sequences and the bidirectional interaction predicted candidate sequences as final candidate sequences; inputting the final candidate sequences into the bidirectional independent sequencing model again to
score, and selecting
a peptide sequence with the highest
score as a prediction result, thereby achieving an effect that
peptide sequence inference can be performed directly from accurate
mass of secondary spectra and primary spectra generated in experiments without a
database, and new peptide
protein discovery is facilitated.