Update README.md
Browse files
    	
        README.md
    CHANGED
    
    | 
         @@ -7,9 +7,9 @@ configs: 
     | 
|
| 7 | 
         
             
            # Description
         
     | 
| 8 | 
         
             
            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" .
         
     | 
| 9 | 
         | 
| 10 | 
         
            -
             
     | 
| 11 | 
         | 
| 12 | 
         
            -
             
     | 
| 13 | 
         | 
| 14 | 
         
             
            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:
         
     | 
| 15 | 
         | 
| 
         | 
|
| 7 | 
         
             
            # Description
         
     | 
| 8 | 
         
             
            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" .
         
     | 
| 9 | 
         | 
| 10 | 
         
            +
            **Protein Format:** SA sequence (AF2)
         
     | 
| 11 | 
         | 
| 12 | 
         
            +
            # Splits
         
     | 
| 13 | 
         | 
| 14 | 
         
             
            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:
         
     | 
| 15 | 
         |