… the quality of the peptides identified by DeepRescore, we used MHC-peptide binding affinity
as a systematic and unbiased quantitative metric and three MHC-peptide binding prediction …

… In this review we discuss the general process of deep learning for peptide identification, …
Deep learning has shown excellent performance with representation learning and the deep …

… against sequences of candidate peptides using database search tools, … peptide-to-spectrum
matches using additional features incorporating deep learning-based predictions of peptide …

… of the peptides. In this manuscript, we present DeepMSPeptide, a bioinformatic tool that
uses a deep learning method to predict proteotypic peptides exclusively based on the peptide …

… for peptide property prediction and peptide/protein identification, provide perspective on
how deep learning solves the associated challenges, and contrast the different deep learning …

… Therefore, we propose DeepACP, a deep learning method combined with the RNN model
and amino-acid character embedding for improving ACP prediction. When performed on the …

… peptides or tandem minigenes, or are only relevant to specific human leukocyte antigen (HLA)
alleles. We apply deep learning to a large (N = 74 patients) HLA peptide … identification of …

… deep learning to de novo peptide sequencing and achieve major breakthroughs on this
well-studied problem. Deep learning … DeepNovo was able to identify peptides that could not be …

… Furthermore, we sought to decipher the underlying mechanisms of peptide–protein interactions
by identifying the peptide-binding residues. We showed that CAMP can accurately detect …

… consideration when identifying the best … peptides is a more important factor than the size
of the search space. Another promising application of deep learning to the peptide identification …