Wilhelmlab/detectability-wang

Detectability - Wang

The dataset contains systematic, quantitative and deep proteome and transcriptome abundance atlas from 29 paired healthy human to serve as a molecular baseline to study human biology.

Dataset Details

• Curated by: Aalborg University - Denmark, in collaboration with Wilhelmlab, TU Munich.
• License: CC0

Dataset Sources

The data is based on the datasets introduced in [1] and available at: https://www.ebi.ac.uk/pride/archive/projects/PXD010154

Uses

The dataset is used for testing detectability prediction models. However, users are free to use or combine the dataset with other datasets for training, fine-tuning, and testing Detectability models.

References

[1] Wang, D., Eraslan, B., Wieland, T., Hallström, B., Hopf, T., Zolg, D. P., ... & Kuster, B. (2019). A deep proteome and transcriptome abundance atlas of 29 healthy human tissues. Molecular systems biology, 15(2), e8503.

Citation

BibTeX:

@article {Abdul-Khalek2024.10.28.620610,
    author = {Abdul-Khalek, Naim and Picciani, Mario and Wimmer, Reinhard and Overgaard, Michael Toft and Wilhelm, Mathias and Echers, Simon Gregersen},
    title = {To fly, or not to fly, that is the question: A deep learning model for peptide detectability prediction in mass spectrometry},
    elocation-id = {2024.10.28.620610},
    year = {2024},
    doi = {10.1101/2024.10.28.620610},
    publisher = {Cold Spring Harbor Laboratory},
    URL = {https://www.biorxiv.org/content/early/2024/10/31/2024.10.28.620610},
    eprint = {https://www.biorxiv.org/content/early/2024/10/31/2024.10.28.620610.full.pdf},
    journal = {bioRxiv}
}

APA:

Abdul-Khalek, N., Picciani, M., Wimmer, R., Overgaard, M. T., Wilhelm, M., & Gregersen Echers, S. (2024). To fly, or not to fly, that is the question: A deep learning model for peptide detectability prediction in mass spectrometry. bioRxiv, 2024-10.‏

Dataset Card Contact

Simon Gregersen, sgr@bio.aau.dk, Department of Chemistry and Biosciences, Aalborg University.

Mathias Wilhelm, mathias.wilhelm@tum.de, Wilhelmlab, TU Munich, School of Life Sciences, Germany.