Open Data for Differential Network Analysis in Glioma

Claire Jean-Quartier*, Fleur Jeanquartier, Andreas Holzinger

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

The complexity of cancer diseases demands bioinformatic techniques and translational research based on big data and personalized medicine. Open data enables researchers to accelerate cancer studies, save resources and foster collaboration. Several tools and programming approaches are available for analyzing data, including annotation, clustering, comparison and extrapolation, merging, enrichment, functional association and statistics. We exploit openly available data via cancer gene expression analysis, we apply refinement as well as enrichment analysis via gene ontology and conclude with graph-based visualization of involved protein interaction networks as a basis for signaling. The different databases allowed for the construction of huge networks or specified ones consisting of high-confidence interactions only. Several genes associated to glioma were isolated via a network analysis from top hub nodes as well as from an outlier analysis. The latter approach highlights a mitogen-activated protein kinase next to a member of histondeacetylases and a protein phosphatase as genes uncommonly associated with glioma. Cluster analysis from top hub nodes lists several identified glioma-associated gene products to function within protein complexes, including epidermal growth factors as well as cell cycle proteins or RAS proto-oncogenes. By using selected exemplary tools and open-access resources for cancer research and differential network analysis, we highlight disturbed signaling components in brain cancer subtypes of glioma
Original languageEnglish
Article number547
Number of pages17
JournalInternational Journal of Molecular Sciences
Volume21
Issue number2
DOIs
Publication statusPublished - Jan 2020

Keywords

  • Astrocytoma
  • Biological data integration
  • Cancer research
  • Differential gene expression
  • Differential network analysis
  • Glioblastoma multiforme
  • Glioma
  • Graph-based analysis
  • Open data
  • Protein-protein interaction

ASJC Scopus subject areas

  • Molecular Biology
  • Spectroscopy
  • Catalysis
  • Inorganic Chemistry
  • Computer Science Applications
  • Physical and Theoretical Chemistry
  • Organic Chemistry

Fields of Expertise

  • Human- & Biotechnology
  • Information, Communication & Computing

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