LORE PMKB-CV

LORE PMKB-CV

• Knowledge graph (LLM-ORE)
  • 70M relations between 8k Diseases (MeSH) and 18k Genes (NCBI, human protein coding) curated by LLMs reading PubMed
  • Data format: (D_id, G_id, PMID, relation) csv file
• Semantic embedding (LLM-EMB)
  • 2.5M DG vectors created by LLMs reading the knowledge graph
  • Data format: (D_id, G_id, vector) pkl file
• DG pathogenicity scores (ML-Ranker)
  • 3.1M DG scores predicted by pretrained models
  • Features, training annotations, pretrained models are also provided
• Curated key semantics taxonomy
  • A manually curated taxonomy of 105 semantic tags about DG pathogenicity in the knowledge graph
  • Use the github LORE Key-Semantics module to use the taxonomy as tags and add them to the knowledge graph

Source project

• https://github.com/ailabstw/LORE
  • Tools for running LLM-ORE relation extraction, LLM-EMB embedding, ML-Ranker prediction, Key-Semantics curation on custom datasets
• https://doi.org/10.1093/bib/bbaf070
  • Research article describing the LORE framework, analyses, experiments, and details of the PMKB-CV dataset