Create README.md

README.md

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+---
+language:
+- en
+license: mit
+tags:
+- Biology
+- Bioinformatics
+- Virus
+- Genomics
+- Proteomics
+- Nucleotide
+- Protein
+- Foundation Model
+- LucaVirus
+- AI4Bio
+- AI4Science
+- Nucleotide-Protein
+task_categories:
+- sequence-modeling
+- feature-xxtraction
+size_categories:
+- 10M<n<100M
+---
+
+# Dataset Card for LucaVirus-OpenVirus-Gene-Prot
+
+## 1. Dataset Summary
+
+**LucaVirus-OpenVirus-Gene-Prot** is the complete, multi-modal **OpenVirus** corpus, curated for the pre-training of the **LucaVirus** biological foundation model. This dataset provides a massive-scale collection of viral sequences, bridging the gap between genomic (nucleotide) and proteomic (protein) data.
+
+The corpus comprises **15.7 million** non-redundant viral sequences, providing a robust foundation for learning the complex language of viral evolution and the "central dogma" of viral biology.
+
+## 2. Dataset Statistics
+
+| Data Type | Count | `obj_type` Identifier |
+| :--- | :--- | :--- |
+| **Nucleotide (Genomes)** | 10.4 Million | `gene` |
+| **Protein (Amino Acids)** | 5.2 Million | `prot` |
+| **Total Sequences** | **15.7 Million** | - |
+
+## 3. Data Structure
+
+The dataset is provided as a compressed **`.tar`** archive. Once extracted, the directory structure follows a standard machine-learning split:
+
+```text
+LucaVirus-OpenVirus-Gene-Prot/
+├── train/          # Training set (primary corpus for pre-training)
+├── dev/            # Validation set (for hyperparameter tuning)
+└── test/           # Test set (for final evaluation)
+```
+
+Each directory contains one or more **CSV files with headers**.
+
+### Data Schema
+Each CSV file includes the following columns:
+
+| Column Name | Description | Details                                                                                                |
+| :--- | :--- |:-------------------------------------------------------------------------------------------------------|
+| **`obj_id`** | Sample ID | Unique identifier for the sample.                                                                                  |
+| **`obj_type`** | Sequence Type | Sequence modality: `gene` (nucleotide) or `prot` (protein).                                                        |
+| **`obj_seq`** | Sequence Content | The raw biological sequence (ATGC for gene; Amino Acids for prot).                                                 |
+| **`obj_label`** | Label | Metadata, taxonomic info, or functional labels associated with the genome and proteins (Annotation, Bio Knowledge) |
+
+## 4. Dataset Intent
+
+This dataset is specifically designed for:
+- **Foundation Model Pre-training**: Building models that can process both DNA/RNA and Protein sequences.
+- **Cross-modal Learning**: Understanding the translation and structural relationships within viral biology.
+- **Viral Research**: A large-scale benchmark for viral sequence classification, functional annotation, and mutation analysis.
+
+## 5. Usage
+
+### Loading with Python
+You can use standard Python libraries to process the data:
+
+```python
+import pandas as pd
+import tarfile
+import os
+
+# Example: Extracting and reading a file
+with tarfile.open("LucaVirus-OpenVirus-Gene-Prot.tar.tar.gz", "r:gz") as tar:
+    tar.extractall(path="./data")
+
+# Read a specific CSV from the train set
+df = pd.read_csv("./data/train/3072_train_1.csv")
+print(df.head())
+```
+
+## 6. Pre-training with LucaVirus
+This dataset is the primary source for the **LucaVirus** model family.   
+- **Full Corpus (Gene + Prot)**: [LucaVirus-OpenVirus-Gene](https://huggingface.co/datasets/LucaGroup/LucaVirus-OpenVirus-Gene)
+- **Protein Subset**: [LucaVirus-OpenVirus-Prot](https://huggingface.co/datasets/LucaGroup/LucaVirus-OpenVirus-Prot)
+- **Models**: Visit the [LucaVirus Collection](https://huggingface.co/collections/LucaGroup/lucavirus).
+
+
+## 7. Citation
+
+If you use this dataset in your research, please cite the following:
+
+```bibtex
+@article{lucavirus2025,
+  title={Predicting the Evolutionary and Functional Landscapes of Viruses with a Unified Nucleotide-Protein Language Model: LucaVirus.},
+  author={Pan, Yuan-Fei* and He, Yong*. et al.},
+  journal={bioRxiv},
+  year={2025},
+  url={https://www.biorxiv.org/content/early/2025/06/20/2025.06.14.659722}
+}
+```
+
+## 8. License
+This dataset is released under the **Apache License 2.0**.
+
+## 9. Contact
+
+---
+*For further information, please visit the [LucaGroup GitHub](https://github.com/LucaOne), email to: [sanyuan.hy@alibaba-inc.com/heyongcsat@gmail.com], or contact the team via the Hugging Face organization profile.*
+
+