README.md

metadata

license: apache-2.0
tags:
  - biology
  - genomics
  - dna
  - eccdna
size_categories:
  - 10K<n<1M
task_categories:
  - token-classification

Real vs. Pseudo-eccDNA Discrimination (Homo sapiens)

This dataset supports the Real vs. Pseudo-eccDNA Discrimination task for human eccDNA.
The goal is to train models that can distinguish true eccDNA sequences from pseudo-eccDNAs
randomly extracted from linear genomic regions with matched length distributions.

Each entry contains:

• sequence: raw eccDNA sequence (A/T/C/G)
• label:
  • 1 → Real eccDNA
  • 0 → Pseudo-eccDNA (negative control)

---

📁 Folder Structure

real_vs_pseudo_eccdna_discrimination_human/
├── data/
│   └── real_vs_pseudo_eccdna_discrimination_human.csv
└── README.md

---

Task Description

True eccDNAs are experimentally verified circular DNA molecules,
whereas pseudo-eccDNAs are generated by randomly extracting linear genomic segments
to match the true eccDNA length distribution.
This task assesses a model’s ability to capture circular topology and regulatory context
beyond simple sequence composition.

---

Citation

If you use this dataset, please cite:

@inproceedings{liu2025eccdnamamba,
  title={eccDNAMamba: A Pre-Trained Model for Ultra-Long eccDNA Sequence Analysis},
  author={Zhenke Liu and Jien Li and Ziqi Zhang},
  booktitle={ICML 2025 GenBio Workshop},
  year={2025},
  url={https://openreview.net/forum?id=56xKN7KJjy}
}