@biocypher

BioCypher

BioCypher is an open-source ecosystem for building, maintaining, and sharing biomedical knowledge graphs (KGs) in a reproducible and FAIR manner. It provides a declarative, ontology-grounded framework that enables researchers to integrate heterogeneous biomedical data sources into harmonised graph structures suitable for analysis, machine learning, and downstream AI workflows.

BioCypher separates schema design, data ingestion, and knowledge graph assembly, supporting transparent and modular workflows that can be adapted across domains. It supports multiple database backends and offers export formats compatible with graph machine learning frameworks. The design emphasises accessibility for both computational experts and bench scientists, supported by strong documentation, tutorials, and community-driven extensions.

Key benefits
  • Ontology-grounded framework for reproducible biomedical knowledge graphs
  • Declarative schema design with modular data ingestion workflows
  • Supports multiple database backends and export formats
  • Compatible with graph analytics and machine learning frameworks
  • Designed for FAIR-compliant knowledge graph construction
  • Accessible to both computational researchers and domain scientists
Applications
  • Integration of heterogeneous biomedical datasets into unified graph structures
  • Construction of knowledge graphs for systems biology and translational research
  • Preparation of graph data for machine learning and AI workflows
  • Reproducible and shareable KG pipelines across research projects
  • Development of interoperable graph-based biomedical infrastructures
Intended use

BioCypher is intended for biomedical researchers, data scientists, and research software engineers who aim to build interoperable, FAIR-compliant knowledge graphs for analysis and AI-driven applications. Basic Python knowledge is recommended; familiarity with biomedical ontologies and knowledge graph concepts is beneficial for advanced use cases.

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Neither development nor maintenance funded by de.NBI