Zhejiang University
Hangzhou, China · 12 authors
Zhejiang University (Hangzhou, China): 12 authors and 29 papers in the de novo peptide sequencing catalog.
Departments
- College of Computer Science and Technology
Papers (29)
- Accurate and ultra-fast de novo HLA-I immunopeptide sequencing with FoxNovo (2026, LangTaoSha (LTS) Preprint)
- MemNovo: Look Back at the Spectrum for Balanced De Novo Peptide Sequencing from Mass Spectrometry (2026, arXiv)
- Regressor-guided Diffusion Model for De Novo Peptide Sequencing with Explicit Mass Control (2026, AAAI 2026)
- A living proteomics benchmark for comprehensive evaluation of deep learning-based de novo peptide sequencing tools (2026, Nature Methods (Registered Report))
- Regressor-guided Diffusion Model for De Novo Peptide Sequencing with Explicit Mass Control (2026, arXiv)
- 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)
- A Comprehensive and Systematic Review for Deep Learning-Based De Novo Peptide Sequencing (2025, IJCAI 2025)
- 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)
- Distilling Non-Autoregressive Model Knowledge for Autoregressive De Novo Peptide Sequencing (2025, OpenReview)
- Bridging the Gap between Database Search and De Novo Peptide Sequencing with SearchNovo (2025, ICLR 2025)
- π-PrimeNovo: an accurate and efficient non-autoregressive deep learning model for de novo peptide sequencing (2025, Nature Communications)
- NovoBench: Benchmarking Deep Learning-based De Novo Sequencing Methods in Proteomics (2024, NeurIPS 2024)
- AdaNovo: Towards Robust De Novo Peptide Sequencing in Proteomics against Data Biases (2024, NeurIPS 2024)
- ReNovo: Retrieval-Based De Novo Mass Spectrometry Peptide Sequencing (2024, ICLR 2025)
- RankNovo: A Universal Reranking Approach for Robust De Novo Peptide Sequencing (2024, OpenReview)
- Bridging the Gap between Database Search and De Novo Peptide Sequencing with SearchNovo (2024, bioRxiv)
- NovoBench: Benchmarking Deep Learning-based De Novo Peptide Sequencing Methods in Proteomics (2024, arXiv)
- PeposX-Exhaust: A lightweight and efficient tool for identification of short peptides (2024, Food Chemistry: X)
- Awesome-Denovo-Peptide-Sequencing (2024, GitHub)
- AdaNovo: Adaptive De Novo Peptide Sequencing with Conditional Mutual Information (2024, arXiv)
- Peposx-Exhaust: A Lightweight and Efficient Tool for Identification of Short Peptides (2023, SSRN Electronic Journal)
- A residual network for de novo peptide sequencing with attention mechanism (2020, 2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV))
- Rapid and Reliable Peptide de Novo Sequencing Facilitated by Microfluidic Chip-Based Edman Degradation (2008, Journal of Proteome Research)