metadata
license: apache-2.0
tags:
- biology
- dna
- reasoning
configs:
- config_name: v1
default: true
data_files:
- split: train
path: train-00000-of-00001.parquet
- split: test
path: test-00000-of-00001.parquet
- config_name: v2
data_files:
- split: train
path: v2/train-00000-of-00001.parquet
- split: test
path: v2/test-00000-of-00001.parquet
- config_name: v3
data_files:
- split: train
path: v3/train-00000-of-00001.parquet
- split: test
path: v3/test-00000-of-00001.parquet
🧬 BioReason
Incentivizing 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.
Configs
v1(default): the release used in the paper.v2: questions give chromosome context only.v3: questions give chromosome and gene context for all variants where a gene is available.
All configs have the same variants, answers, sequences and train/test splits.
Usage
from datasets import load_dataset
dataset = load_dataset("wanglab/variant_effect_coding", "v1") # or "v2", "v3"
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},
}