Datasetpublic

wanglab/variant_effect_coding

🧬 BioReasonIncentivizing Multimodal Biological Reasoning within a DNA-LLM Model Variant Effect Coding Dataset 50,083 core variant entries from GPN-MSA study using ClinVar pathogenic variants and gnomAD benign variants (MAF>5%), split by chromosome (Chr 1-7,9-22,X,Y for train, Chr 8 for test) for pathogenic/benign classification. Usage from datasets import load_dataset dataset = load_dataset("wanglab/variant_effect_coding") example =… See the full description on the dataset page: https://huggingface.co/datasets/wanglab/variant_effect_coding.

sourceHugging Faceapache-2.0updated 1y agoView on Hugging Face

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Dataset Card

<h1 align="center"> 🧬 BioReason<br>Incentivizing Multimodal Biological Reasoning within a DNA-LLM Model </h1>

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Variant Effect Coding Dataset

50,083 core variant entries from GPN-MSA study using ClinVar pathogenic variants and gnomAD benign variants (MAF>5%), split by chromosome (Chr 1-7,9-22,X,Y for train, Chr 8 for test) for pathogenic/benign classification.

Usage

python

from datasets import load_dataset

dataset = load_dataset("wanglab/variant_effect_coding")
example = dataset["train"][0]
print(example)

Citation

@misc{fallahpour2025bioreasonincentivizingmultimodalbiological,
      title={BioReason: Incentivizing Multimodal Biological Reasoning within a DNA-LLM Model}, 
      author={Adibvafa Fallahpour and Andrew Magnuson and Purav Gupta and Shihao Ma and Jack Naimer and Arnav Shah and Haonan Duan and Omar Ibrahim and Hani Goodarzi and Chris J. Maddison and Bo Wang},
      year={2025},
      eprint={2505.23579},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2505.23579}, 
}