Synthyra/bernett_gold_ppi

Leakage-free "gold" standard PPI dataset

From Bernett, et al, found in

Cracking the black box of deep sequence-based protein–protein interaction prediction

• paper
• code

and

Deep learning models for unbiased sequence-based PPI prediction plateau at an accuracy of 0.65

• paper
• code

Description

This is a balanced binary protein-protein interaction dataset with positives from HIPPIE and paritioned with KaHIP. 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.

Note:

Q96PU5 is not located in the provided SwissProt fasta file but is used in the train split several times. We added this before data processing so no rows were dropped.

Example use

def get_ppi_data():
    data = load_dataset("Synthyra/bernett_gold_ppi").shuffle(seed=42)
    data = data.remove_columns(['A', 'B'])
    return data['train'], data['valid'], data['test']

Please cite

Please cite their figshare dataset and papers if you use this dataset.