pyBiodatafuse: extending interoperability of data using modular queries across biomedical resources

Bioinformatics, vol. 42

Abstract

MOTIVATION: Integrating omics data analysis with publicly available databases is crucial for unravelling complex biological mechanisms. However, this integration process is often intricate and time-consuming due to the diversity and complexity of the data involved. Achieving consistent harmonization across data types is challenging when managing disparate formats and sources. To address these issues, we introduce pyBiodatafuse, a query-based Python tool designed to integrate biomedical databases. This tool establishes a modular framework that simplifies data wrangling, enabling the creation of context-specific knowledge graphs (KGs) while supporting graph-based analyses. RESULTS: We developed a pipeline for generating context-specific knowledge graphs dynamically, allowing users to create KGs on the fly from a set of gene or metabolite identifiers. pyBiodatafuse features a user-friendly interface that streamlines this process, making it accessible even to researchers without extensive computational expertise. Additionally, the tool offers plugins for widely used platforms such as Cytoscape, Neo4j, and GraphDB, enabling local hosting of resulting property and RDF graphs. This versatility ensures that generated KGs can be efficiently utilized within diverse research workflows. To demonstrate its potential, we used pyBiodatafuse to create a graph for post-COVID syndrome using differential gene expression data, showcasing its ability to build adaptable and context-specific knowledge representations. Thus, pyBiodatafuse sets the stage for streamlined data integration, empowering researchers to focus on discovery and analysis without being hindered by data management complexities. AVAILABILITY AND IMPLEMENTATION: pyBiodatafuse is open-source, with its source code and PyPi package available at https://github.com/BioDataFuse/pyBiodatafuse and https://pypi.org/project/pyBiodatafuse/. The user interface can be accessed at https://biodatafuse.org/. Additionally, a release has been made on Zenodo at https://doi.org/10.5281/zenodo.18468942.

Authors 10

1. Yojana Gadiya corresponding
   Affiliation as printed

   Enveda , Boulder, Colorado, 80301,

2. Javier Millán Acosta

   Maastricht University

   Affiliation as printed

   Department of Translational Genomics, NUTRIM Institute of Nutrition and Translational Research in Metabolism, Maastricht University , Maastricht, 6229,

3. Ammar Ammar

   Maastricht University

   Affiliation as printed

   Department of Translational Genomics, NUTRIM Institute of Nutrition and Translational Research in Metabolism, Maastricht University , Maastricht, 6229,

4. Alejandro Adriaque Lozano

   Maastricht University

   Affiliation as printed

   Maastricht Centre for Systems Biology (MaCSBio), Maastricht University , Maastricht, 6229,

5. Delano Wetstede Aachen Faculty of Life Science & Technology

   University of Applied Sciences Leiden

   Affiliation as printed

   Faculty of Life Science & Technology, Leiden University of Applied Sciences , Leiden, 2333,

6. Dominik Martinát

   Palacký University Olomouc

   Affiliation as printed

   Department of Physical Chemistry , Palacky University , Olomouc, 779 00,

7. Ana Claudia Sima

   SIB Swiss Institute of Bioinformatics

   Affiliation as printed

   SIB Swiss Institute of Bioinformatics , Lausanne, 1015,

8. Hailiang Mei Aachen Sequencing Analysis Support Core

   Leiden University Medical Center

   Affiliation as printed

   Sequencing Analysis Support Core, Leiden University Medical Center (LUMC) , Leiden, 2333,

9. Egon Willighagen

   Maastricht University

   Affiliation as printed

   Department of Translational Genomics, NUTRIM Institute of Nutrition and Translational Research in Metabolism, Maastricht University , Maastricht, 6229,

10. Tooba Abbassi‐Daloii corresponding

    Maastricht University · Amsterdam University Medical Centers · University of Amsterdam

    Affiliation as printed

    Department of Medical Biology, University of Amsterdam, Amsterdam UMC , Amsterdam, North Holland, 1105,

    Department of Translational Genomics, NUTRIM Institute of Nutrition and Translational Research in Metabolism, Maastricht University , Maastricht, 6229,