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Datasets:
PatSnap
/
patent-linked-siRNA

Tasks:
Feature Extraction
Modalities:
Tabular
Text
Formats:
json
Languages:
English
Size:
1M - 10M
Tags:
biology
siRNA
oligonucleotide-therapeutics
chemical-modification
sequence-modeling
patent
Libraries:
Datasets
pandas
Polars
License:
Dataset card Data Studio Files
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metadata 
license: cc-by-4.0
task_categories:
  - feature-extraction
language:
  - en
tags:
  - biology
  - siRNA
  - oligonucleotide-therapeutics
  - chemical-modification
  - sequence-modeling
  - patent
pretty_name: Patent-linked modified siRNA sequences
size_categories:
  - 1M<n<10M

🧬 Dataset Summary

Patent-linked nucleotide sequence records focused RNAi therapeutics patent portfolio. Each record pairs a raw nucleotide sequence with its source patent number, publication date, and global patent family coverage.

🚀 Key Features

  • Patent Linkage: Each sequence is tied to a patent number (pn) and publication date (pbdt), enabling sequence-to-IP traceability.
  • Global Family Coverage: family_country lists all jurisdictions in the patent family (e.g., US, EP, CN, JP, WO).
  • Patent Status: status field tracks the current patent lifecycle state.
  • Modification Tracking: modified_info captures amendment history where available (~8.6% of records).

💻 Quick Start & MCP Integration

from datasets import load_dataset

dataset = load_dataset("your-org/alnylam-sequences", split="train")
print(dataset[0]["sequence"])
# Output: 'atcacacgcacacacaaaagaag'
print(dataset[0]["pn"])
# Output: 'EP4416284A1'
print(dataset[0]["family_country"])
# Output: ['JP', 'NZ', 'EA', 'SG', 'CN', 'MX', 'AU', 'IN', 'US', 'EP', 'WO', 'HK', 'IL', 'ZA', 'CA', 'KR']

🔗 Resources