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--- |
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dataset_info: |
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features: |
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- name: Sequences |
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dtype: string |
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- name: Classes |
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dtype: int64 |
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- name: Proteins |
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dtype: string |
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splits: |
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- name: test |
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num_bytes: 9104480 |
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num_examples: 190955 |
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download_size: 5167867 |
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dataset_size: 9104480 |
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configs: |
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- config_name: default |
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data_files: |
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- split: test |
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path: data/test-* |
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license: cc |
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--- |
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# Detectability - Wang |
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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. |
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## Dataset Details |
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- **Curated by:** Aalborg University - Denmark, in collaboration with Wilhelmlab, TU Munich. |
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- **License:** [CC0](https://creativecommons.org/public-domain/cc0/) |
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### Dataset Sources |
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The data is based on the datasets introduced in [[1]](#ref1) and available at: https://www.ebi.ac.uk/pride/archive/projects/PXD010154 |
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## Uses |
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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. |
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## References |
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<a id="ref1">[1]</a> 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. |
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## Citation |
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**BibTeX:** |
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```bibtex |
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@article {Abdul-Khalek2024.10.28.620610, |
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author = {Abdul-Khalek, Naim and Picciani, Mario and Wimmer, Reinhard and Overgaard, Michael Toft and Wilhelm, Mathias and Echers, Simon Gregersen}, |
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title = {To fly, or not to fly, that is the question: A deep learning model for peptide detectability prediction in mass spectrometry}, |
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elocation-id = {2024.10.28.620610}, |
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year = {2024}, |
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doi = {10.1101/2024.10.28.620610}, |
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publisher = {Cold Spring Harbor Laboratory}, |
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URL = {https://www.biorxiv.org/content/early/2024/10/31/2024.10.28.620610}, |
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eprint = {https://www.biorxiv.org/content/early/2024/10/31/2024.10.28.620610.full.pdf}, |
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journal = {bioRxiv} |
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} |
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``` |
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**APA:** |
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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. |
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## Dataset Card Contact |
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Simon Gregersen, sgr@bio.aau.dk, Department of Chemistry and Biosciences, Aalborg University. |
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Mathias Wilhelm, mathias.wilhelm@tum.de, Wilhelmlab, TU Munich, School of Life Sciences, Germany. |