ASO Atlas

A comprehensive dataset of 188,521 RNase H-mediated antisense oligonucleotides (ASOs) with experimentally validated efficacy measurements, extracted from 417 USPTO patents published between 2001 and 2025.

Overview

ASO Atlas provides the first large-scale, publicly available resource for understanding the relationship between ASO sequence, chemical modifications, and inhibitory activity. The dataset includes:

• 188,521 gapmer ASOs targeting 306 human genes
• Sequence composition and target genomic locations
• Chemical modification patterns (phosphorothioate backbones, 2'-MOE, cEt sugar modifications)
• Quantitative efficacy measurements from qRT-PCR experiments across multiple cell lines
• Experimental metadata including cell type, dosage, and transfection method

Installation

git clone https://github.com/barneyhill/aso_atlas.git
cd aso_atlas
pip install -r requirements.txt

Quick Start

import pandas as pd

# Load the dataset
df = pd.read_pickle('data/aso_atlas.pkl')

# View schema
print(df.columns)
# ['aso_sequence_5_to_3', 'inhibition_percent', 'chemistry', 'custom_id', 
#  'target_mrna', 'target_gene', 'cell_line', 'dosage', 
#  'cells_per_well', 'transfection_method', ...]

Related Resources

• Preprint: https://www.biorxiv.org/content/10.1101/2025.10.29.685292v1
• OligoAI Model: https://huggingface.co/barneyhill/OligoAI
• OligoAI Training Code: https://github.com/barneyhill/OligoAI
• Web Interface: https://sitlabs.org/OligoAI