BiomarkerKB: An integrated knowledgebase supporting biomarker-centric exploration of biomedical data

Biomarkers are essential tools for disease detection, risk assessment, therapeutic monitoring, and precision medicine. However, biomarker data are dispersed across heterogeneous resources, inconsistently reported in the literature, and rarely standardized for computational use. This fragmentation limits reproducibility, cross-study integration, and the discovery of novel biomarker and disease relationships. We developed BiomarkerKB, designed to harmonize and integrate biomarker information under a standardized data model. The model captures both core fields (biomarker entity, disease/condition, and exposure agent) and contextual metadata (specimen, biomarker role, evidence, and provenance). Biomarker data and related annotations were either curated from publications or collected from public resources. The initial release of BiomarkerKB contains over 200,000 biomarker-disease associations spanning genes, proteins, metabolites, glycans, and chemical elements. BiomarkerKB data were ingested into a Neo4j-based knowledge graph that comprises more than 300,000 nodes and 1.2 million edges. A publicly accessible web portal provides a unified framework for biomarker knowledge exploration and discovery.