National Center for Protein Sciences (Beijing)
Beijing, China · 9 authors
National Center for Protein Sciences (Beijing) (Beijing, China): 9 authors and 18 papers in the de novo peptide sequencing catalog.
Departments
- State Key Laboratory of Medical Proteomics
Papers (18)
- π-MNovo improves de novo peptide sequencing through microbial-domain adaptation and evidence-guided candidate selection (2026, bioRxiv)
- AI proteomics: from protein identification to virtual cells (2026, Nature Methods)
- False discovery rate control for trustworthy AI-based de novo peptide sequencing (2026, bioRxiv)
- π-HelixNovo2: Making Accurate Online De Novo Peptide Sequencing Available to All (2026, Genomics, Proteomics & Bioinformatics)
- π-MSNet: A billion-scale, AI-ready living proteomics data portal (2026, bioRxiv)
- A living proteomics benchmark for comprehensive evaluation of deep learning-based de novo peptide sequencing tools (2026, Nature Methods (Registered Report))
- DiNovo enables high-coverage and high-confidence de novo peptide sequencing via mirror proteases and deep learning (2026, Nature Communications)
- DiNovo: high-coverage, high-confidence de novo peptide sequencing using mirror proteases and deep learning (2025, bioRxiv)
- π-PrimeNovo: an accurate and efficient non-autoregressive deep learning model for de novo peptide sequencing (2025, Nature Communications)
- Transforming de novo peptide sequencing by explainable AI (2024, Research Square)
- π-PrimeNovo: an accurate and efficient non-autoregressive deep learning model for de novo peptide sequencing (2024, bioRxiv)
- ContraNovo: A Contrastive Learning Approach to Enhance De Novo Peptide Sequencing (2024, AAAI 2024)
- Introducing π-HelixNovo for practical large-scale de novo peptide sequencing (2024, Briefings in Bioinformatics)
- Introducing PandaNovo for practical large-scale de novo peptide sequencing (2023, bioRxiv)
- PGPointNovo: an efficient neural network-based tool for parallel de novo peptide sequencing (2023, Bioinformatics Advances)
- Precision De Novo Peptide Sequencing Using Mirror Proteases of Ac-LysargiNase and Trypsin for Large-scale Proteomics (2019, Molecular & Cellular Proteomics)
- MRUniNovo: an efficient tool for de novo peptide sequencing utilizing the Hadoop distributed computing framework (2017, Bioinformatics)
- Algorithm Development of de novo Peptide Sequencing Via Tandem Mass Spectrometry (2010, Progress in Biochemistry and Biophysics)