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@@ -51,6 +51,10 @@ Deep learning models for unbiased sequence-based PPI prediction plateau at an ac
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  ## Description
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  This is a balanced binary protein-protein interaction dataset with positives from [HIPPIE](https://cbdm-01.zdv.uni-mainz.de/~mschaefer/hippie/) and paritioned with [KaHIP](https://kahip.github.io/). There are no sequence overlaps in splits, furthermore, they are split based on a maximum CD-HIT of 40% pairwise sequence similarity. Node degree bias was also reduced.
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  ## Example use
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  ```python
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  def get_ppi_data():
 
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  ## Description
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  This is a balanced binary protein-protein interaction dataset with positives from [HIPPIE](https://cbdm-01.zdv.uni-mainz.de/~mschaefer/hippie/) and paritioned with [KaHIP](https://kahip.github.io/). There are no sequence overlaps in splits, furthermore, they are split based on a maximum CD-HIT of 40% pairwise sequence similarity. Node degree bias was also reduced.
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+ Note:
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+
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+ [Q96PU5](https://www.uniprot.org/uniprotkb/Q96PU5) is not located in the provided SwissProt fasta file but is used in the train split several times. We added this before dataprocessing so no rows were dropped.
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  ## Example use
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  ```python
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  def get_ppi_data():