Fudan University
Shanghai, China, Shanghai · 20 authors
Fudan University (Shanghai, China, Shanghai): 20 authors and 22 papers in the de novo peptide sequencing catalog.
Departments
- Department of Chemistry
- Department of Otolaryngology, Eye & ENT Hospital
- Department of Pathology, Zhongshan Hospital
- Research Institute of Intelligent Complex Systems
Papers (22)
- AI proteomics: from protein identification to virtual cells (2026, Nature Methods)
- A living proteomics benchmark for comprehensive evaluation of deep learning-based de novo peptide sequencing tools (2026, Nature Methods (Registered Report))
- XA-Novo: an accurate and high-throughput mass spectrometry-based de novo sequencing technology for monoclonal antibodies and antibody mixtures (2026, Nature Communications)
- Accurate de novo sequencing of the modified proteome with OmniNovo (2025, arXiv)
- Bidirectional Representations Augmented Autoregressive Biological Sequence Generation (2025, NeurIPS 2025)
- Bidirectional Representations Augmented Autoregressive Biological Sequence Generation (2025, arXiv)
- Universal Biological Sequence Reranking for Improved De Novo Peptide Sequencing (2025, ICML 2025)
- Curriculum Learning for Biological Sequence Prediction: The Case of De Novo Peptide Sequencing (2025, ICML 2025)
- MassNet: billion-scale AI-friendly mass spectral corpus enables robust de novo peptide sequencing (2025, bioRxiv)
- Curriculum Learning for Biological Sequence Prediction: The Case of De Novo Peptide Sequencing (2025, arXiv)
- Universal Biological Sequence Reranking for Improved De Novo Peptide Sequencing (2025, arXiv)
- XA-Novo: an accurate and high-throughput mass spectrometry-based de novo sequencing technology for monoclonal antibodies and antibody mixtures (2025, Research Square)
- Distilling Non-Autoregressive Model Knowledge for Autoregressive De Novo Peptide Sequencing (2025, OpenReview)
- Decoding Protein Glycosylation by an Integrative Mass Spectrometry-Based De Novo Sequencing Strategy (2025, JACS Au)
- π-PrimeNovo: an accurate and efficient non-autoregressive deep learning model for de novo peptide sequencing (2025, Nature Communications)
- RankNovo: A Universal Reranking Approach for Robust De Novo Peptide Sequencing (2024, OpenReview)
- Comprehensive assembly of monoclonal and mixed antibody sequences (2024, bioRxiv)
- 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)
- Isolation and Characterization of Marine Brevibacillus sp. S-1 Collected from South China Sea and a Novel Antitumor Peptide Produced by the Strain (2014, PLoS ONE)
- Enhancing TOF/TOF-based de Novo Sequencing Capability for High Throughput Protein Identification with Amino Acid-Coded Mass Tagging (2005, Journal of Proteome Research)
- Sequence Pattern Correlation of Amino Acid in Collision‐induced Dissociation Electrospray Ionization Mass Spectrometry (2002, Chinese Journal of Chemistry)