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---
license: mit
---

# Dataset Card for VirBiCla-training

VirBiCla is a ML-based viral DNA detector designed for long-read sequencing metagenomics.

This dataset is a support dataset for training the base ML model.

## Dataset Details

### Dataset Description

- **Curated by:** [Astra Bertelli](https://astrabert.vercel.app/)
- **License:** MIT License

### Dataset Sources [optional]

<!-- Provide the basic links for the dataset. -->

- **Repository:** [GitHub repository for VirBiCla](https://github.com/AstraBert/VirBiCla)

## Uses

This dataset is intended as support for training the base VirBiCla model


## Dataset Structure

Dataset is a CSV file composed of 60.003 record sequences (coming from RefSeq 16S bacterial rRNA, 18S fungal rRNA, SSU eukaryotic rRNA and RefSeq viral genomes) evaluated on 13 features.

Features are:

- Domain
- A, T, C and G proportion
- Percentage of A, T, C and G homopolimeric regions
- Gene density
- Entropy
- Effective Number of Codons (codon usage metrics)

## Dataset Creation

Find everything that is needed for Dataset creation on [VirBiCla website](https://astrabert.github.io/VirBiCla)

## Bias, Risks, and Limitations

The dataset is mainly directed towards amplicon-sequencing and long-read sequencing, which are the best use cases for VirBiCla.


## Citation

Please consider cite the author of this work (Astra Bertelli) and VirBiCla [GitHub repository](https://github.com/AstraBert/VirBiCla) when using this dataset or the associated model.