De novo peptide sequencing by deep learning

Our method, DeepNovo, introduces deep learning to de novo peptide sequencing from tandem MS data, the key technology for protein characterization in proteomics research. DeepNovo achieves major improvement of sequencing accuracy over state of the art methods and subsequently enables complete assembly of protein sequences without assisting databases. Our model is retrainable to adapt to any sources of data and provides a complete end-to-end training and prediction solution, an important feature given the growing massive amount of data. Our study also presents an innovative approach to combine deep learning and dynamic programming to solve optimization problems.