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