Table of Contents

• Introduction
  • Mission Statement
• User Experiences
  • A Knowledge Graph for Impact of Genomic Variation on Function (IGVF)
  • Drug Repurposing with CROssBAR
  • Builing a Knowledge Graph for Contextualised Metabolic-Enzymatic Interactions
• Get Involved!
• Installation
  • Install as a dependency for your KG pipeline
  • For developers
• Configuration
  • BioCypher settings
  • Neo4j settings
  • PostgreSQL settings
• Quickstart
  • The host module adapter
  • The schema configuration YAML file
  • The biocypher configuration YAML file
• Adapters
  • BioCypher meta-graph
• BioCypher Tutorial - Basics
  • Setup
  • Configuration
  • Section 1: Adding data
  • Section 2: Merging data
  • Section 3: Handling properties
  • Section 4: Handling relationships
• BioCypher Tutorial - Handling Ontologies
  • What is an ontology?
  • How BioCypher uses ontologies
  • Visualising ontologies
  • Using ontologies: plain Biolink
  • Model extensions
  • Hybridising ontologies
• BioCypher Tutorial - Adapters
  • Adapter philosophy
  • Adapter functions
  • 1. Loading the Data
  • 2. Passing the Data
  • Note: Strict mode
• Interacting with Neo4j
  • Communication via the Neo4j Python Driver
  • Interacting with a running Neo4j instance
  • Exporting for the neo4j-admin import feature
  • Translating between original and BioCypher vocabulary
• Tutorial - Neo4j
• R and Bioconductor
• Submodule documentation
  • _core.py: The main BioCypher interface
  • _write.py: Write the Graph to various formats for batch import
  • _connect.py: On-line functionality for interaction with a DBMS
  • _mapping.py: Mapping of data inputs to KG ontology
  • _ontology.py: Ontology ingestion, parsing, and manipulation
  • _create.py: Base classes for node and edge representations in BioCypher
  • _translate.py: Translation functionality for implemented types of representation
  • _logger.py: Logging
  • _misc.py: Miscellaneous utility functions