8 citations · 12 across the 3 of their papers we have counts for
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q-bio.QM2024★ 2 cited
NovoBench: Benchmarking Deep Learning-based De Novo Peptide Sequencing Methods in Proteomics
Jingbo Zhou, Shaorong Chen, Jun Xia +6
Tandem mass spectrometry has played a pivotal role in advancing proteomics, enabling the high-throughput analysis of protein composition in biological tissues. Many deep learning m…
q-bio.QM2024★ 2 cited
AdaNovo: Adaptive \emph{De Novo} Peptide Sequencing with Conditional Mutual Information
Jun Xia, Shaorong Chen, Jingbo Zhou +4
Tandem mass spectrometry has played a pivotal role in advancing proteomics, enabling the analysis of protein composition in biological samples. Despite the development of various d…
q-bio.QM2023★ 8 cited
ContraNovo: A Contrastive Learning Approach to Enhance De Novo Peptide Sequencing
Zhi Jin, Sheng Xu, Xiang Zhang +6
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…