---
license: cc0-1.0
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
dataset_info:
  features:
  - name: sequence
    dtype: string
  - name: modified_sequence
    dtype: string
  - name: precursor_mz
    dtype: float64
  - name: precursor_charge
    dtype: int64
  - name: mz_array
    sequence: float64
  - name: intensity_array
    sequence: float32
  splits:
  - name: train
    num_bytes: 839098224
    num_examples: 499402
  - name: validation
    num_bytes: 49792990
    num_examples: 28572
  - name: test
    num_bytes: 300840334
    num_examples: 111312
  download_size: 1414788031
  dataset_size: 1189731548
---


# Dataset Card for Nine-Species excluding Yeast
Dataset used for the baseline comparison of InstaNovo to other models.


## Dataset Description

- **Repository:** [InstaNovo](https://github.com/instadeepai/InstaNovo)
- **Paper:** [InstaNovo enables diffusion-powered de novo peptide sequencing in large-scale proteomics experiments](https://www.nature.com/articles/s42256-025-01019-5) 

### Dataset Summary

Dataset used in the original [DeepNovo](https://www.pnas.org/doi/full/10.1073/pnas.1705691114) paper. 
- The training set contains 8 species excluding yeast
- The validation/test set contains the yeast species

## Dataset Structure

The dataset is tabular, where each row corresponds to a labelled MS2 spectra.
- `sequence (string)` \
  The target peptide sequence excluding post-translational modifications
- `modified_sequence (string)` \
  The target peptide sequence including post-translational modifications
- `precursor_mz (float64)` \
  The mass-to-charge of the precursor (from MS1)
- `charge (int64)` \
  The charge of the precursor (from MS1)
- `mz_array (list[float64])` \
  The mass-to-charge values of the MS2 spectrum
- `mz_array (list[float32])` \
  The intensity values of the MS2 spectrum

## Citation Information

If you use this dataset, please cite the original authors.
The original data is available on [MASSIVE](https://massive.ucsd.edu/ProteoSAFe/static/massive.jsp) with the identifier `MSV000081382`.

Please also cite InstaNovo:

```bibtex
@article{eloff_kalogeropoulos_2025_instanovo,
        title        = {InstaNovo enables diffusion-powered de novo peptide sequencing in large-scale
                        proteomics experiments},
        author       = {Eloff, Kevin and Kalogeropoulos, Konstantinos and Mabona, Amandla and Morell,
                        Oliver and Catzel, Rachel and Rivera-de-Torre, Esperanza and Berg Jespersen,
                        Jakob and Williams, Wesley and van Beljouw, Sam P. B. and Skwark, Marcin J.
                        and Laustsen, Andreas Hougaard and Brouns, Stan J. J. and Ljungars,
                        Anne and Schoof, Erwin M. and Van Goey, Jeroen and auf dem Keller, Ulrich and
                        Beguir, Karim and Lopez Carranza, Nicolas and Jenkins, Timothy P.},
        year         = 2025,
        month        = {Mar},
        day          = 31,
        journal      = {Nature Machine Intelligence},
        doi          = {10.1038/s42256-025-01019-5},
        issn         = {2522-5839},
        url          = {https://doi.org/10.1038/s42256-025-01019-5}
}
```