Tumor-Biomarker Knowledge Graph
A weighted heterogeneous knowledge graph containing four types of entities (Tumor, Biomarker, Drug, and ADR)  extracted from MEDLINE corpus for adverse drug reaction discovery in antitumor drugs. TBKG uses a naive  Bayesian model to explore correlations and provides explainable predictions through tumor-biomarker-drug  pathways. The knowledge graph contains 1,179 tumors, 2,550 biomarkers, 1,806 drugs, and 756 ADRs with six  types of relationships totaling 139,254 edges.
[]
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{"activity_status": "active", "category": "KnowledgeGraph", "creation_date": "2025-11-22T00:00:00Z", "description": "A weighted heterogeneous knowledge graph containing four types of entities (Tumor, Biomarker, Drug, and ADR)  extracted from MEDLINE corpus for adverse drug reaction discovery in antitumor drugs. TBKG uses a naive  Bayesian model to explore correlations and provides explainable predictions through tumor-biomarker-drug  pathways. The knowledge graph contains 1,179 tumors, 2,550 biomarkers, 1,806 drugs, and 756 ADRs with six  types of relationships totaling 139,254 edges.", "domains": ["drug discovery", "pharmacology", "biomedical", "clinical", "systems biology"], "homepage_url": "https://www.frontiersin.org/articles/10.3389/fgene.2020.625659/full", "id": "tbkg", "last_modified_date": "2026-07-02T00:00:00Z", "layout": "resource_detail", "license": {"id": "https://creativecommons.org/licenses/by/4.0/", "label": "CC BY 4.0", "logo": "http://mirrors.creativecommons.org/presskit/buttons/80x15/png/by.png"}, "name": "Tumor-Biomarker Knowledge Graph", "products": [{"category": "GraphProduct", "description": "Weighted heterogeneous knowledge graph extracted from MEDLINE corpus containing 1,179 tumors, 2,550 biomarkers, 1,806 drugs, and 756 ADRs with 139,254 relationship edges (Tumor-Biomarker, Tumor-Drug, Tumor-ADR, Drug-Biomarker, Drug-ADR, Biomarker-ADR). Includes correlation weights calculated using naive Bayesian model.", "format": "mixed", "id": "tbkg.data", "name": "TBKG Knowledge Graph Data", "original_source": [{"relation_type": "prov:hadPrimarySource", "source": "tbkg"}, {"relation_type": "prov:wasDerivedFrom", "source": "pubmed"}], "product_url": "https://www.frontiersin.org/articles/10.3389/fgene.2020.625659/full#supplementary-material", "secondary_source": [{"relation_type": "prov:wasInfluencedBy", "source": "umls"}]}, {"category": "Product", "description": "Clinical validation dataset with calculated ADRs for osimertinib ranked by importance, biomarker pathways explaining drug-ADR relationships, and clinical data from 8 lung adenocarcinoma patients. Model achieved Kappa=0.68 concordance with official manual and 0.81 three-fold cross-validation accuracy.", "format": "mixed", "id": "tbkg.osimertinib_case_study", "name": "TBKG Osimertinib ADR Case Study Data", "original_source": [{"relation_type": "prov:hadPrimarySource", "source": "tbkg"}, {"relation_type": "prov:wasDerivedFrom", "source": "pubmed"}], "product_url": "https://www.frontiersin.org/articles/10.3389/fgene.2020.625659/full#supplementary-material", "secondary_source": [{"relation_type": "prov:wasInfluencedBy", "source": "umls"}]}], "publications": [{"authors": ["Wang M", "Ma X", "Si J", "Tang H", "Wang H", "Li T", "Ouyang W", "Gong L", "Tang Y", "He X", "Huang W", "Liu X"], "doi": "10.3389/fgene.2020.625659", "id": "https://www.ncbi.nlm.nih.gov/pubmed/33584816", "journal": "Front Genet", "preferred": true, "title": "Adverse Drug Reaction Discovery Using a Tumor-Biomarker Knowledge Graph", "year": "2020"}], "repository": "https://www.frontiersin.org/articles/10.3389/fgene.2020.625659/full#supplementary-material", "taxon": ["NCBITaxon:9606"]}