Improvements to Casanovo, a Deep Learning De Novo Peptide Sequencer
peer-reviewed · Journal of Proteome Research · 2025
peer-reviewed · Journal of Proteome Research · 2025. Gwenneth Straub et al.
| Date | 2025-12-30 |
| Type | peer-reviewed |
| Venue | Journal of Proteome Research |
| Publisher | American Chemical Society (ACS) |
| Contribution | algorithm |
| DOI | 10.1021/acs.jproteome.5c00706 |
| Citations (OpenAlex) | 4 |
| Venue 2-year citedness | 3.48 |
Preprint version: Improvements to CasaNovo, a deep learning de novo peptide sequencer (2025-07-25, bioRxiv)
Methods and tools
- Casanovo: First Transformer
Cites (10)
- Deep Learning Methods for De Novo Peptide Sequencing (2024) crossref
- NovoBoard: A Comprehensive Framework for Evaluating the False Discovery Rate and Accuracy of De Novo Peptide Sequencing (2024) crossref
- Accounting for Digestion Enzyme Bias in Casanovo (2024) crossref
- Sequence-to-sequence translation from mass spectra to peptides with a transformer model (2024) crossref
- Algorithms for de-novo sequencing of peptides by tandem mass spectrometry: A review (2023) crossref
- BiATNovo: A Self-Attention based Bidirectional Peptide Sequencing Method (2023) crossref
- De novo mass spectrometry peptide sequencing with a transformer model (2022) crossref
- De novo sequencing of proteins by mass spectrometry (2020) crossref
- Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning (2019) crossref
- De novo peptide sequencing by deep learning (2017) crossref
Cited by (3)
- CasanovoGUI: a cross-platform desktop application for deep learning-based de novo peptide sequencing with Casanovo (2026) crossref
- False discovery rate control for trustworthy AI-based de novo peptide sequencing (2026) crossref
- Learning Fragmentation Physics or Exploiting Sequence Priors? Benchmarking Bias in Deep Learning Models for De Novo Peptide Sequencing (2026) crossref