University of Chinese Academy of Sciences
Beijing, China, Hangzhou · 47 authors
University of Chinese Academy of Sciences (Beijing, China, Hangzhou): 47 authors and 25 papers in the de novo peptide sequencing catalog.
Departments
- School of Pharmaceutical Science and Technology, Hangzhou Institute for Advanced Study
Papers (25)
- Ancient proteins identify various Denisovan remains from Southwest China (2026, Nature)
- Accurate and ultra-fast de novo HLA-I immunopeptide sequencing with FoxNovo (2026, LangTaoSha (LTS) Preprint)
- AI proteomics: from protein identification to virtual cells (2026, Nature Methods)
- Enamel proteins from six Homo erectus specimens across China (2026, Nature)
- A large-scale unified deep learning model for peptide mass spectrum interpretation trained on multimodal data (2026, Nature Machine Intelligence)
- 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)
- The proteome of the late Middle Pleistocene Harbin individual (2025, Science)
- pUniFind: a unified large pre-trained deep learning model pushing the limit of mass spectra interpretation (2025, arXiv)
- DiNovo: high-coverage, high-confidence de novo peptide sequencing using mirror proteases and deep learning (2025, bioRxiv)
- Decoding Protein Glycosylation by an Integrative Mass Spectrometry-Based De Novo Sequencing Strategy (2025, JACS Au)
- Characterization of natural peptides in Pheretima by integrating proteogenomics and label-free peptidomics (2023, Journal of Pharmaceutical Analysis)
- Denovo-GCN: De Novo Peptide Sequencing by Graph Convolutional Neural Networks (2023, Applied Sciences (MDPI))
- Accurate discrimination of leucine and isoleucine residues by combining continuous digestion with multiple MS3 spectra integration in protein sequence (2022, Talanta)
- Full-length Protein Sequencing Based on Continuous Digestion Using Non-specific Proteases (2021, Acta Chimica Sinica)
- Deep Learning in Proteomics (2020, Proteomics)
- pNovo 3: precise de novo peptide sequencing using a learning-to-rank framework (2019, Bioinformatics)
- Precision De Novo Peptide Sequencing Using Mirror Proteases of Ac-LysargiNase and Trypsin for Large-scale Proteomics (2019, Molecular & Cellular Proteomics)
- pSite: Amino Acid Confidence Evaluation for Quality Control of De Novo Peptide Sequencing and Modification Site Localization (2017, Journal of Proteome Research)
- NIPTL-Novo: Non-isobaric peptide termini labeling assisted peptide de novo sequencing (2017, Journal of Proteomics)
- Open-pNovo: De Novo Peptide Sequencing with Thousands of Protein Modifications (2017, Journal of Proteome Research)
- Identification of phosphopeptides with unknown cleavage specificity by a de novo sequencing assisted database search strategy (2014, PROTEOMICS)
- De novo identification and quantification of single amino-acid variants in human brain (2014, Journal of Molecular Cell Biology)
- pNovo+: De Novo Peptide Sequencing Using Complementary HCD and ETD Tandem Mass Spectra (2013, Journal of Proteome Research)
- pNovo: De novo Peptide Sequencing and Identification Using HCD Spectra (2010, Journal of Proteome Research)