| license: mit | |
| viewer: True | |
| # Description | |
| Subcellular Localization prediction is a 10-class classification task to predict where a protein locates in the cell, where each input protein *x* is mapped to a label *y* ∈ {0, 1, ..., 9}. | |
| # Splits | |
| **Structure type:** AF2 | |
| The dataset is from [**DeepLoc: prediction of protein subcellular localization using deep learning**](https://academic.oup.com/bioinformatics/article/33/21/3387/3931857). We employ all proteins (proteins that lack AF2 structures are removed), and split them based on 70% structure similarity (see [ProteinShake](https://github.com/BorgwardtLab/proteinshake/tree/main)), with the number of training, validation and test set shown below: | |
| - Train: 10414 | |
| - Valid: 1368 | |
| - Test: 1368 | |
| # Label | |
| 0: Nucleus | |
| 1: Cytoplasm | |
| 2: Extracellular | |
| 3: Mitochondrion | |
| 4: Cell.membrane | |
| 5: Endoplasmic.reticulum | |
| 6: Plastid | |
| 7: Golgi.apparatus | |
| 8: Lysosome/Vacuole | |
| 9: Peroxisome | |