| license: mit | |
| # Description | |
| Binary Localization prediction is a binary classification task where each input protein *x* is mapped to a label *y* ∈ {0, 1}, corresponding to either "membrane-bound" or "soluble" . | |
| # 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: 6707 | |
| - Valid: 698 | |
| - Test: 807 | |
| # Label | |
| 0: membrane-bound | |
| 1: soluble | |