---
license: apache-2.0
multilingual: false
---

# Scorpio-Gene-Taxa Dataset: Curated Gene Sequences for Model Training and Evaluation

## Protein and DNA Sequences Available for Evaluating DNA and Protein Language Models for Gene and Taxonomy Prediction

This dataset was created using the Woltka pipeline to compile the **Basic Genome Dataset**, containing 4,634 genomes. Each genus is represented by a single genome, with a focus on bacteria and archaea. Viruses and fungi were excluded due to insufficient gene information.

Key steps in data preparation:
1. Gene names were used to filter and group protein-coding sequences; unnamed genes with hypothetical or unknown functions were excluded.
2. Only genes with more than 1,000 named instances (497 genes) were included to improve reliability for training.

## Dataset Description
- **DNA**
- **Protein**
- **Genera**2,046

### Dataset Splits (dataset_type)

#### **Train**
- **Description**: Contains sequences used for model training.

#### **Test**
- **Description**: Contains sequences from the same genus and gene as the training set but uses different sequences.
- **Purpose**: Evaluates sequence-level generalization.

#### **Taxa_out**
- **Description**: Excludes sequences from 18 phyla present in the training set.
- **Purpose**: Evaluates gene-level generalization.

#### **Gene_out**
- **Description**: Excludes 60 genes present in the training set but keeps sequences within the same phyla.
- **Purpose**: Evaluates taxonomic-level generalization.

## Citation

```bibtex
@article{refahi2025enhancing,
  title={Enhancing nucleotide sequence representations in genomic analysis with contrastive optimization},
  author={Refahi, Mohammadsaleh and Sokhansanj, Bahrad A and Mell, Joshua C and Brown, James R and Yoo, Hyunwoo and Hearne, Gavin and Rosen, Gail L},
  journal={Communications Biology},
  volume={8},
  number={1},
  pages={517},
  year={2025},
  publisher={Nature Publishing Group UK London}
}