README.md

metadata

license: apache-2.0
language:
  - en
tags:
  - chemistry
pretty_name: medea_db

MEDEA-DB

This database contains curated databases and pre-trained model weights across multiple domains of tools leveraged by Medea, including:

• PPI networks & Multi-scale gene/protein embeddings (PINNACLE, TranscriptFormer, etc.)
• Gene correlation and dependency statistics (Chronos gene-effect profiles from DepMap 24Q2 CRISPR)
• Immunotherapy response prediction model checkpoints (COMPASS pretrain checkpoint)

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Available Data & Resources

1. Gene/Protein Embeddings

PINNACLE Embeddings (pinnacle_embeds/)

• Model: PINNACLE
• Files:
  • pinnacle_protein_embed.pth: Protein-level embeddings with cell type specificity
  • pinnacle_mg_embed.pth: Meta-graph level embeddings on cellular interactions and tissue hierarchy
  • ppi_embed_dict.pth: PPI-based embeddings
  • pinnacle_labels_dict.txt: Gene/protein labels
• Config Names: pinnacle_protein_embed, labels_dict
• Format: PyTorch tensors

Transcriptformer Embeddings (transcriptformer_embedding/)

• Model: Transcriptformer (Transcriptomics transformer)
• Structure:
  • embedding_generation/: Scripts for generating embeddings
  • embedding_store/: Pre-computed embeddings (138 .npy files)
• Format: NumPy arrays, compressed archives

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2. Gene Dependency & Correlation Data

DepMap 24Q2 (depmap_24q2/)

• Release: DepMap Public 24Q2
• Files:
  • corr_matrix.npy: Gene correlation matrix
  • p_val_matrix.npy: Statistical significance values
  • p_adj_matrix.npy: Adjusted p-values (multiple testing correction)
  • gene_correlations.h5: HDF5 format correlations
  • gene_idx_array.npy: Gene index mappings
  • gene_names.txt: Gene identifiers

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3. Immunotherapy Response Prediction Models

COMPASS Checkpoints (compass/checkpoint/)

• Model: COMPASS
• Checkpoints:
  • pretrainer.pt: Pre-trained base model
  • pft_leave_IMVigor210.pt: Leave-one-cohort-out (IMVigor210) fintuned model

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Data Sources & Citations

Please cite the original sources when using specific datasets or models.

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License

This dataset is released under the CC BY-NC-SA 4.0 license.