3 accepted papers
Tandem mass spectrometry (MS/MS) has revolutionized the field of proteomics, enabling the high-throughput identification of proteins. However, one of the central challenges in mass spectrometry-based proteomics remains peptide identification, especially in the absence of a comprehensive peptide data
De novo peptide sequencing from mass spectrometry (MS) data is a critical task in proteomics research. Traditional de novo algorithms have encountered a bottleneck in accuracy due to the inherent complexity of proteomics data. While deep learning-based methods have shown progress, they reduce the pr…
Tandem mass spectrometry has played a pivotal role in advancing proteomics, enabling the analysis of protein composition in biological tissues. Many deep learning methods have been developed for \emph{de novo} peptide sequencing task, i.e., predicting the peptide sequence for the observed mass spect…