BioPAX-Explorer: a Python Object-Oriented framework for overcoming the complexity of querying biological networks

Abstract

MotivationBiological Pathway Exchange (BioPAX) is a standard language, represented in OWL, that aims to enable the integration, exchange, visualization and analysis of biological pathway data. While public databanks increasingly provide datasets in BioPAX format, their use remains below potential. Users may encounter challenges in harnessing the data due to the BioPAX intricately detailed underlying model. Moreover, extracting data demands specific technical skills, posing a barrier for many potential users. ResultsTo address these obstacles, we developped BioPAX-Explorer. This toolis designed to facilitate the adoption and usage of BioPAX for extracting data or build algorithms and models, within the Python community. BioPAX-Explorer is a Python package that provides an object-oriented data model automatically generated from the BioPAX OWL specification. Moreover, it offers expressive query capabilities that shield users from BioPAX inner complexity. BioPAX-Explorer supports dataset building features, validation facilities and pre-build queries. It simplifies the extraction and processing of data from BioPAX sources by automatically generating SPARQL queries. BioPAX-Explorer also offers a user-friendly interface for Python users, allowing exhaustive exploration of large datasets through features such as memory-efficient query execution, entity-oriented queries without the need for SPARQL knowledge. It also allows to learn and reuse complex SPARQL queries for biological network analysis. Additionally, BioPAX-Explorer can accelerate the development of Python-based network analysis software, since it generates graph data structures from BioPAX queries and facilitates the creation of transparent, reproducible workflows based on the BioPAX OWL standard. Availability and implementationBioPAX-Explorer is freely available. We provide the source code, documentation, installation instructions and a Jupyter notebook with tutorial at https://fjrmoreews.github.io/biopax-explorer/