SaProtHub/Dataset-Subcellular_Localization-DeepLoc
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 Protein Format: SA sequence (AF2) The dataset is from DeepLoc: prediction of protein subcellular localization using deep learning. We employ all proteins (proteins that lack AF2 structures are removed), and split them based on 70% structure similarity (see… See the full description on the dataset page: https://huggingface.co/datasets/SaProtHub/Dataset-Subcellular_Localization-DeepLoc.
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1---2license: mit3configs:4- config_name: dataset5 data_files: "dataset.csv"6---7# Description8Subcellular 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}.9 10# Splits11 12**Protein Format:** SA sequence (AF2)13 14The 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:15 16- Train: 1041417- Valid: 136818- Test: 136819 20# Label21 220: Nucleus23 241: Cytoplasm25 262: Extracellular27 283: Mitochondrion29 304: Cell.membrane31 325: Endoplasmic.reticulum33 346: Plastid35 367: Golgi.apparatus37 388: Lysosome/Vacuole39 409: Peroxisome41