Update README.md

The OpenGenome2 was published as part of [Genome modeling and design across all domains of life with Evo 2](https://www.biorxiv.org/content/10.1101/2025.02.18.638918v1). Please refer to this paper for a more detailed description of the dataset and processing procedure.

## Dataset Summary

**OpenGenome2** is a massive, highly curated genomic atlas containing 8.84 trillion DNA base pairs, spanning all domains of life. It represents a significant expansion of the original [OpenGenome](https://huggingface.co/datasets/InstaDeepAI/OpenGenome) dataset, increasing the total number of nucleotides from 300 billion to nearly 9 trillion.

This dataset was compiled to train **Evo 2**, a 40-billion parameter biological foundation model with a 1 million token context window. The dataset is designed to provide a comprehensive and representative view of genomic diversity, enabling models to learn the fundamental "language" of DNA. It includes prokaryotic, eukaryotic, metagenomic, and organelle sequences, with a specific focus on augmenting data around likely functional regions to improve performance on downstream biological tasks.

The primary purpose of OpenGenome2 is for the **unsupervised pre-training** of large-scale biological foundation models. The model trained on this data, Evo 2, is capable of:
* **Zero-shot Variant Effect Prediction:** Predicting the functional impacts of genetic variations without task-specific fine-tuning.
* **Controllable Sequence Generation:** Generating novel genomic sequences (mitochondrial, prokaryotic, eukaryotic) with specific desired properties.
* **Fill-in-the-Middle (Masked Genome Modeling):** Reconstructing missing segments of DNA sequences.

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## Source Data

The data was aggregated and curated from numerous public biological databases:

* **Prokaryotic Genomes:** [Genome Taxonomy Database (GTDB)](https://gtdb.ecogenomic.org/) releases v214.1 and v220.0.
* **Eukaryotic Genomes:** [NCBI](https://www.ncbi.nlm.nih.gov/refseq/) Reference Sequences (RefSeq).
* **Metagenomes:** NCBI, JGI IMG, MGnify, MG-RAST, Tara Oceans samples, and others.
* **Organelle Genomes:** NCBI Organelle resource.
* **Noncoding RNA:** Ensembl, Rfam, and RNAcentral.
* **Promoters:** EPDnew database.

Extensive filtering, de-duplication, and quality control measures were applied, including clustering by average nucleotide identity (ANI) to select representative genomes, removing short or low-quality contigs, and filtering redundant metagenomic contigs based on protein clusters. The processing process is described in more details in [Brixi et al., section 4.2.2.](https://www.biorxiv.org/content/10.1101/2025.02.18.638918v1).

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## Additional Information

### Licensing Information

The dataset is released under the **Apache License 2.0**.

### Citation Information

If you use this dataset in your research, please cite the following paper:
```bibtex


@article
{brixi2025genome,
title={Genome modeling and design across all domains of life with Evo 2},
author={Brixi, Garyk and Durrant, Matthew G and Ku, Jerome and Poli, Michael and Brockman, Greg and Chang, Daniel and Gonzalez, Gabriel A and King, Samuel H and Li, David B and Merchant, Aditi T and others},
journal={BioRxiv},
pages={2025--02},
year={2025},
publisher={Cold Spring Harbor Laboratory}
}

README.md

@@ -1,3 +1,18 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+task_categories:
+- text-generation
+- fill-mask
+language:
+- en
+tags:
+- genomics
+- biology
+- foundation-model
+- dna
+- huggingscience
+- science
+pretty_name: OpenGenome2
+size_categories:
+- n>1T
+---