metadata

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

Dataset for operon identification in bacteria (DNA)

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

The operon annotations have been extracted from Operon DB and the genome DNA sequences have been extracted from GenBank. Each row contains whole bacterial genome, represented by a list of DNA 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-dna", split="test")
item = ds[0]

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

# fetch gene DNA sequences of an operon
contig_idx = 0
operon_gene_dna_seqs = [
  item['dna_sequence'][contig_idx][item[contig_idx]['start'][i] - 1: item[contig_idx]['end'][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 coding sequence representation of the genome see the bacbench-operon-identification-protein-sequences 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: dna_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: 51309243 num_examples: 11 download_size: 23962298 dataset_size: 51309243 configs: - config_name: default data_files: - split: test path: data/test-*