Datasets:
File size: 1,497 Bytes
7f8d0d5 4dbcee8 7f8d0d5 ca464e5 7f8d0d5 ca464e5 7f8d0d5 ca464e5 7f8d0d5 ca464e5 7f8d0d5 ca464e5 7f8d0d5 ca464e5 7f8d0d5 ca464e5 32f3841 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 | ---
license: cc-by-4.0
pretty_name: Therapeutic Targets & Genomic Loci
tags:
- genomics
- drug-targets
- bioinformatics
- ensembl
- ncbi
task_categories:
- feature-extraction
size_categories:
- 1K<n<10K
---
🎯 **Dataset Summary**
A drug target reference database covering 2,000 biological targets with cross-database identifier mapping and drug association counts. Designed for target-centric drug discovery and multi-omics integration.
**🚀 Key Features**
- **Cross-Database IDs:** Each target links UniProt, NCBI Gene ID, Ensembl Gene ID, and RefSeq accessions (nucleotide and protein).
- **Multilingual Names & Aliases:** `target_name` and `alias` support both English gene symbols and Chinese nomenclature.
- **Drug Count:** `drug_count` provides a quick measure of target druggability based on associated compounds.
**💻 Quick Start & MCP Integration**
```python
from datasets import load_dataset
dataset = load_dataset("your-org/drug-targets", split="train")
record = dataset[0]
en_name = next(n["name"] for n in record["target_name"] if n["lang"] == "EN")
print(en_name)
# Output: 'solute carrier family 37 member 4'
print(record["uniprot_id"])
# Output: ['O43826']
print(record["drug_count"])
# Output: 1
```
## 🔗 Resources
- **Developer Portal**: [open.patsnap.com](https://open.patsnap.com)
- **PatSnap Life Sciences**: [patsnap.com/solutions/life-sciences](https://www.patsnap.com/solutions/life-sciences/)
- **GitHub**: [github.com/patsnap](https://github.com/patsnap) |