metadata

license: apache-2.0
tags:
  - biology
  - bacteria
  - operons
  - genomics
  - genomes
  - proteins
pretty_name: Dataset for identifying operons in bacterial genomes (protein sequences)
size_categories:
  - n<1K

Dataset for operon identification in bacteria (Protein sequences)

A dataset of 4,073 operons across 11 bacterial genomes species.

The operon annotations have been extracted from Operon DB and the genome protein sequences have been extracted from GenBank. Each row contains a set of protein sequences present in the genome, represented by a list of protein sequences from different contigs.

We extracted high-confidence (i.e. known) operons from Operon DB, filtered out non-contigous operons and only kept genomes with at least 9 known operons. We then matched the operon annotations with the genomes available in GenBank using gene names provided by Operon DB.

Labels

For each operon, we provide the operon protein indices (operon_protein_indices column) which can be used to extract the genes which form an operon. We also include operon names and gene names as metadata.

Usage

We recommend loading the dataset in a streaming mode to prevent memory errors.

from datasets import load_dataset


ds = load_dataset("macwiatrak/bacbench-operon-identification-protein-sequences", split="test")
item = ds[0]

# fetch operon protein indices
operon_prot_indices = item["operon_protein_indices"]
operon_prot_names = item["operon_protein_names"]

# fetch gene protein sequences of an operon
contig_idx = 0
operon_gene_prot_seqs = [
  item['protein_sequence'][contig_idx][i] for i in operon_prot_indices[contig_idx][0]
]

Split

We recommend using operon identification dataset is a fully unsupervised manner, therefore, the entire dataset makes up a test set.

See github repository for details on how to embed the dataset with DNA and protein language models as well as code to evaluate operon identification in a zero-shot fasion. For DNA sequence representation of the genome see the bacbench-operon-identification-dna dataset.

dataset_info: features: - name: taxid dtype: string - name: strain_name dtype: string - name: contig_name sequence: string - name: accession_id dtype: string - name: gene_name sequence: sequence: string - name: protein_name sequence: sequence: string - name: old_protein_name sequence: sequence: string - name: start sequence: sequence: int64 - name: end sequence: sequence: int64 - name: strand sequence: sequence: int64 - name: protein_sequence sequence: sequence: string - name: operon_protein_names sequence: sequence: sequence: string - name: operon_protein_indices sequence: sequence: sequence: int64 - name: operon_names sequence: sequence: string - name: n_operons dtype: int64 splits: - name: test num_bytes: 16707131 num_examples: 11 download_size: 15258914 dataset_size: 16707131 configs: - config_name: default data_files: - split: test path: data/test-*