Nature Machine Intelligence
5 papers in the catalog
5 de novo peptide sequencing papers published in Nature Machine Intelligence, catalogued with authors, methods and citation counts.
| 2-year mean citedness | 19.94 |
| h-index | 146 |
| Works indexed | 1256 |
From OpenAlex. The 2-year mean citedness is computed the same way as the Journal Impact Factor, but over the open citation graph.
Papers
- A large-scale unified deep learning model for peptide mass spectrum interpretation trained on multimodal data (2026, peer-reviewed)
- InstaNovo enables diffusion-powered de novo peptide sequencing in large-scale proteomics experiments (2025, peer-reviewed)
- Mitigating the missing-fragmentation problem in de novo peptide sequencing with a two-stage graph-based deep learning model (2023, peer-reviewed)
- Computationally instrument-resolution-independent de novo peptide sequencing for high-resolution devices (2021, peer-reviewed)
- Personalized deep learning of individual immunopeptidomes to identify neoantigens for cancer vaccines (2020, peer-reviewed)