Relating Bionty to other tools#
Biological ontologies are structured frameworks that define and categorize biological entities along with the relationships that connect them. Knowledge graphs, built upon these ontologies, extend this concept by creating interconnected networks of biological entities, fostering a holistic understanding of complex biological systems. Here, we will describe the similarities and differences between Bionty and other tools.
Mapping against biological ontologies streamlines data interpretation and communication by establishing a common vocabulary and framework, facilitating accurate cross-disciplinary analysis and knowledge exchange within the realm of biological research.
Bionty is a Python package that provides unified access to biological ontologies. It further provides an API to curate biological metadata in standalone mode and as an SQL plugin as part of the Lamin platform by mapping against ontologies. To enable the curation of previously unexplored biological data, Bionty can be extended with custom in-house ontologies. Bionty is not designed to build ontologies or knowledge graphs.
Knowledge graphs in the life sciences are information networks that capture complex relationships and connections between various biological entities. By representing data in a graph-like structure, they enable researchers to enhance understanding of the intricate interactions that drive biological systems.
Biocypher is a Python package that simplifies the creation of knowledge graphs. Built upon a modular framework, Biocypher empowers users to manipulate and harmonize ontologies. Biocypher does not focus on data curation or SQL entities and is primarily for developers interested in building their own knowledge graphs.