Ensemble-GNN: federated ensemble learning with graph neural networks for disease module discovery and classification.

Journal: Bioinformatics (Oxford, England)
Published Date: Nov 1, 2023

Abstract

SUMMARY: Federated learning enables collaboration in medicine, where data is scattered across multiple centers without the need to aggregate the data in a central cloud. While, in general, machine learning models can be applied to a wide range of data types, graph neural networks (GNNs) are particularly developed for graphs, which are very common in the biomedical domain. For instance, a patient can be represented by a protein-protein interaction (PPI) network where the nodes contain the patient-specific omics features. Here, we present our Ensemble-GNN software package, which can be used to deploy federated, ensemble-based GNNs in Python. Ensemble-GNN allows to quickly build predictive models utilizing PPI networks consisting of various node features such as gene expression and/or DNA methylation. We exemplary show the results from a public dataset of 981 patients and 8469 genes from the Cancer Genome Atlas (TCGA).

Authors

  • Bastian Pfeifer
    Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria.
  • Hryhorii Chereda
    Medical Bioinformatics, University Medical Center Göttingen, Göttingen, Germany.
  • Roman Martin
    Faculty of Mathematics and Computer Science, University of Marburg, Hans-Meerwein-Str. 6, D-35032, Marburg, Lahn, Germany.
  • Anna Saranti
    Human-Centered AI Lab, Institute of Forest Engineering, Department of Forest and Soil Sciences, University of Natural Resources and Life Sciences Vienna, 1190 Wien, Austria.
  • Sandra Clemens
    Data Science in Biomedicine, Department of Mathematics and Computer Science, University of Marburg, Marburg 35043, Germany.
  • Anne-Christin Hauschild
    IBM Life Sciences Discovery Centre, Princess Margaret Cancer Centre, Toronto, ON, Canada; Department of Computer Science, University of Toronto, Toronto, ON, Canada; University Health Network, Toronto, ON, Canada.
  • Tim Beissbarth
    3 Department of Medical Statistics, University Medical Center Goettingen, Goettingen, Germany.
  • Andreas Holzinger
    Human-Centered AI Lab, Medical University of Graz, Graz, Austria.
  • Dominik Heider
    Department of Mathematics and Computer Science, University of Marburg, Marburg, Germany.

Keywords

External Resources

Popular Topics
Recent Journals