Educators:
Sebastian Lobentanzer (Associated member), Johann Dreo, Claire Laudy, Matthieu Najm, Edwin Carreno, Inga Ulusoy
Date:
15-19.06.2026
Location:
Heidelberg, Im Neuenheimer Feld 205
Contents:
Many modern biomedical methods benefit from the availability of prior knowledge, for example about genes, proteins, or diseases. Knowledge graphs, i.e., representations of prior knowledge in machine-readable graph form, have become the quasi-standard for storing, manipulating, and sharing biomedical prior knowledge. To meet the needs of broad user communities in generating knowledge graphs, we have developed BioCypher, a modular framework for the creation of knowledge graphs based on ontologies, targeting single cell and spatial omics, microbiomics, metabolomics, and various multi-omics modelling and machine learning methods.
In this workshop, we will learn about knowledge representations, knowledge graphs, ontologies, and data structures, and put this knowledge to practical use with BioCypher. The workshop will also contain a module on information fusion, leveraging OntoWeaver to combine data from different sources and joining this information into one single graph. Further, we will learn how to utilize generative AI to upscale to more complex projects.
Learning goals:
(1) How to create knowledge graphs from “your” data and import them into a graph database for further studies. (2) Fundamental principles of research software development, communal open-source software development and using AI agents in coding. (3) Approaches in information fusion and data harmonization.
Prerequisites:
Basic Python knowledge, Laptop with Python installation / IDE
Keywords:
Knowledge graphs, Biomedical science, Ontologies, Knowledge extraction, Information fusion, Agentic automation
Tools:
BioCypher, OntoWeaver, Croissant, GitHub Copilot / Claude / Cursor / ...
Contact:
Inga Ulusoy,
Website & Registration:
https://biocypher.org/community/2026-workshop/