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@@ -47,4 +47,68 @@ configs:
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  path: data/test-*
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  license: apache-2.0
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  pretty_name: Dataset for predicting protein-protein interactions in bacterial genomes
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  path: data/test-*
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  license: apache-2.0
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  pretty_name: Dataset for predicting protein-protein interactions in bacterial genomes
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+ tags:
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+ - biology
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+ - protein
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+ - PPI
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+ - genomics
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+ - STRING-DB
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+ - bacteria
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+ - interactome
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+ size_categories:
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+ - n<1K
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+ ---
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+
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+ # Dataset for protein-protein interaction prediction across bacteria (Protein sequences)
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+
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+ A dataset of 261 bacterial genomes across 215 genera with protein-protein interaction (PPI) scores for each genome.
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+
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+ The genome protein sequences and PPI scores have been extracted from [STRING DB](https://string-db.org/).
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+ Each row contains a set of protein sequences from a genome, ordered by their location on the chromosome and plasmids and a set of associated PPI scores.
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+ The PPI scores have been extracted using the `combined` score from STRING DB.
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+
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+
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+ The interaction between two proteins is represented by a triple: `[prot1_index, prot2_index, score]`. Where to get a probability score, you must divide the score by `1000`
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+ (i.e. if the score is `721` then to get a true score do `721/1000=0.721`). The index of a protein refers to the index of the protein in the `protein_sequences` column of the
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+ row. See example below in [Usage](#usage)
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+
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+
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+ ## Usage
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+ We recommend loading the dataset in a streaming mode to prevent memory errors.
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+ ```python
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+ from datasets import load_dataset
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+
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+
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+ ds = load_dataset("macwiatrak/bacbench-ppi-stringdb-protein-sequences-small", split="validation", streaming=True)
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+ item = next(iter(ds))
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+
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+ # select a contig_idx
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+ contig_idx = 0
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+ # fetch protein sequences from a genome (list of strings) for the contig_idx
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+ prot_seqs = item["protein_sequence"][contig_idx]
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+ # fetch PPI triples labels (i.e. [prot1_index, prot2_index, score])
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+ ppi_triples = item["labels"][contig_idx]
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+
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+ # get protein seqs and label for one pair of proteins
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+ prot1 = prot_seqs[ppi_triples[0][0]]
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+ prot2 = prot_seqs[ppi_triples[0][1]]
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+ score = ppi_triples[0][2] / 1000
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+
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+ # we recommend binarizing the labels based on the threshold of 0.6
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+ binary_ppi_triples = [
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+ (prot1_index, prot2_index, int((score / 1000) >= 0.6)) for prot1_index, prot2_index, score in ppi_triples
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+ ]
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+ ```
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+
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+ ## Split
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+
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+ We provide a phylogeny-aware `train`, `validation` and `test` split by genus with proportions of `60 / 10 / 20` (%) respectively as part of the dataset.
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+ This means that the the genera in train, validation and test do not overlap.
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+
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+ See [github repository](https://github.com/macwiatrak/Bacbench) for details on how to embed the dataset with DNA and protein language models as well as code to predict
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+ protein-protein interactions.
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+
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+ ## Relevant resources:
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+
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+ * Equivalent dataset with DNA rather than protein sequences - https://huggingface.co/datasets/macwiatrak/bacbench-ppi-stringdb-dna-small
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+ * Full dataset of bacterial organisms with associated PPI from STRING DB (10,533 genomes) - https://huggingface.co/datasets/macwiatrak/bacbench-ppi-stringdb-protein-sequences