license: mit
viewer: false
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}.
The digital label means:
0: Nucleus
1: Cytoplasm
2: Extracellular
3: Mitochondrion
4: Cell.membrane
5: Endoplasmic.reticulum
6: Plastid
7: Golgi.apparatus
8: Lysosome/Vacuole
9: Peroxisome
Splits
Structure type: 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 ProteinShake), with the number of training, validation and test set shown below:
- Train: 10414
- Valid: 1368
- Test: 1368
Data format
We organize all data in LMDB format. The architecture of the databse is like:
length: The number of samples
0:
name: The UniProt ID of the protein
seq: The structure-aware sequence
label: classification label of the sequence
1:
···