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perturblab/
scelmo-drugs-gpt-3.5

Name: scelmo-drugs-gpt-3.5
Availability: InStock

embedding_extractor

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scELMo Drug Embeddings

This directory contains drug embeddings generated using scELMo methodology.

Source

These embeddings are converted from the official scELMo repository: https://github.com/HelloWorldLTY/scELMo

Model Information

Model: gpt-3.5-turbo
Embedding Dimension: 1536
Type: drug
Aggregation Mode: wa
API Model: text-embedding-ada-002

Files

gene_embeddings.pkl: Gene embeddings dictionary in PerturbLab format
- Format: {'embeddings': {gene_name: embedding_array}, 'gene_list': [gene_names]}
config.json: Model configuration

Usage

python

from perturblab.model.scelmo import scELMoModel

# Load model
model = scELMoModel.from_pretrained('scelmo-drugs-gpt-3.5')

# Use embeddings
embeddings = model.predict_embeddings(adata, aggregation_mode='wa')

Citation

If you use these embeddings, please cite the original scELMo paper:

bibtex

@article{liu2023scelmo,
  title={scELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis},
  author={Liu, Tianyu and Chen, Tianqi and Zheng, Wangjie and Luo, Xiao and Zhao, Hongyu},
  journal={Cell Patterns (in press)},
  pages={2023--12},
  year={2025},
  publisher={Cell Press}
}

perturblab/scelmo-drugs-gpt-3.5