A unifying framework for biomedical research knowledge graphs

ai-ready biochatter bioinformatics biomedical framework knowledge-graph neo4j ontology postgresql rdf rdfs retrieval-augmented-generation sql
3 Open Issues Need Help Last updated: Jul 25, 2025

Open Issues Need Help

View All on GitHub

A unifying framework for biomedical research knowledge graphs

Python
#ai-ready#biochatter#bioinformatics#biomedical#framework#knowledge-graph#neo4j#ontology#postgresql#rdf#rdfs#retrieval-augmented-generation#sql

AI Summary: This feature request proposes the development of a tool that generates a Neo4j GraphQL Library-compatible GraphQL schema directly from a BioCypher schema file. This would automate the creation of a GraphQL API for BioCypher knowledge graphs, ensuring consistency between the BioCypher data model and the exposed API, and overcoming limitations of Neo4j's introspection tool.

Complexity: 4/5
good first issue workshop

A unifying framework for biomedical research knowledge graphs

Python
#ai-ready#biochatter#bioinformatics#biomedical#framework#knowledge-graph#neo4j#ontology#postgresql#rdf#rdfs#retrieval-augmented-generation#sql

AI Summary: The BioCypher Python package has a bug where a `NameError` occurs due to an optional dependency (scirpy) not being properly handled in type annotations. The task is to fix this bug by either removing the type annotation referencing the optional dependency's class (`AirrCell`) or making `scirpy` a mandatory dependency, ensuring the code functions correctly regardless of whether `scirpy` is installed.

Complexity: 3/5
bug good first issue

A unifying framework for biomedical research knowledge graphs

Python
#ai-ready#biochatter#bioinformatics#biomedical#framework#knowledge-graph#neo4j#ontology#postgresql#rdf#rdfs#retrieval-augmented-generation#sql