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Interactive Visualization of Gene Regulatory Networks with Associated Gene Expression Time Series Data

  • Michel A. Westenberg
  • Sacha A. F. T. van Hijum
  • Andrzej T. Lulko
  • Oscar P. Kuipers
  • Jos B. T. M. Roerdink
Part of the Mathematics and Visualization book series (MATHVISUAL)

Summary

We present GENeVis, an application to visualize gene expression time series data in a gene regulatory network context. This is a network of regulator proteins that regulate the expression of their respective target genes. The networks are represented as graphs, in which the nodes represent genes, and the edges represent interactions between a gene and its targets. GENeVis adds features that are currently lacking in existing tools, such as mapping of expression value and corresponding p-value (or other statistic) to a single visual attribute, multiple time point visualization, and visual comparison of multiple time series in one view. Various interaction mechanisms, such as panning, zooming, regulator and target highlighting, data selection, and tooltips support data analysis and exploration. Subnetworks can be studied in detail in a separate view that shows the network context, expression data plots, and tables containing the raw expression data. We present a case study, in which gene expression time series data acquired in-house are analyzed by a biological expert using GENeVis. The case study shows that the application fills the gap between present biological interpretation of time series experiments, performed on a gene-by-gene basis, and analysis of global classes of genes whose expression is regulated by regulator proteins.

Keywords

Gene Regulatory Network Carbon Catabolite Repression Layout Algorithm Time Series Experiment Multiple Time Series 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [AMA07]
    D. Archambault, T. Munzner, and D. Auber. TopoLayout: Multi-level graph layout by topological features. IEEE Trans. Visualization and Computer Graphics, 13(2):305–317, 2007.CrossRefGoogle Scholar
  2. [BBO+06]
    D. W. J. Bosman, E.-J. Blom, P. J. Ogao, O. P. Kuipers, and J. B. T. M. Roerdink. MOVE: A multi-level ontology-based visualization and exploration framework for genomic networks. In Silico Biology, 7:0004, 2006.Google Scholar
  3. [BBvH+07]
    E. J. Blom, D. W. J. Bosman, S. A. F. T. van Hijum, R. Breitling, L. Tijsma, R. Silvis, J. B. T. M. Roerdink, and O. P. Kuipers. FIVA: Functional information viewer and analyzer extracting biological knowledge from transcriptome data of prokaryotes. Bioinformatics, page btl658, 2007.Google Scholar
  4. [BETT99]
    G. Di Battista, P. Eades, R. Tamassia, and I. G. Tollis. Graph Drawing: Algorithms for the Visualization of Graphs. Prentice Hall, New Jersey, 1999.zbMATHGoogle Scholar
  5. [BHL+03]
    H. M. Blencke, G. Homuth, H. Ludwig, U. Mader, M. Hecker, and J. Stulke. Transcriptional profiling of gene expression in response to glucose in Bacillus subtilis : Regulation of the central metabolic pathways. Metabolic Engineering, 5(2):133–149, 2003.CrossRefGoogle Scholar
  6. [BSRG06]
    M. Baitaluk, M. Sedova, A. Ray, and A. Gupta. BiologicalNetworks: Visualization and analysis tool for systems biology. Nucleic Acids Research, 34:W466–W471, 2006. Web Server Issue.CrossRefGoogle Scholar
  7. [BST03]
    B.-J. Breitkreutz, C. Stark, and M. Tyers. Osprey: A network visualization system. Genome Biology, 4(3):R22, 2003.CrossRefGoogle Scholar
  8. [Gil06]
    D. Gilbert. JFreeChart. http://www.jfree.org/jfreechart, 2006.
  9. [HCL05]
    J. Heer, S. K. Card, and J. A. Landay. Prefuse: a toolkit for interactive information visualization. In CHI ’05: Proc. SIGCHI conf. Human factors in computing systems, pages 421-430, 2005.Google Scholar
  10. [HMM00]
    I. Herman, G. Melançon, and M. S. Marshall. Graph visualization and navigation in information visualization: a survey. IEEE Trans. Visualization and Computer Graphics, 6(1):24–43, 2000.CrossRefGoogle Scholar
  11. [HMW+ 05]
    Z. Hu, J. Mellor, J. Wu, T. Yamada, D. Holloway, and C. DeLisi. VisANT: Data-integrating visual framework for biological networks and modules. Nucleic Acids Research, 33:W352-W357, 2005. Web Server Issue.Google Scholar
  12. [HMWD04]
    Z. Hu, J. Mellor, J. Wu, and C. DeLisi. VisANT: An online visualization and analysis tool for biological interaction data. BMC Bioinformatics, 5:17, 2004.CrossRefGoogle Scholar
  13. [LBKK07]
    A. T. Lulko, G. Buist, J. Kok, and O. P. Kuipers. Transcriptome analysis of temporal regulation of carbon metabolism by CcpA in Bacillus subtilis reveals additional target genes. Journal of Molecular Microbiology and Biotechnology, 12(1-2):82–95, 2007.CrossRefGoogle Scholar
  14. [LCB+05]
    G. L. Lorca, Y. J. Chung, R. D. Barabote, W. Weyler, C. H. Schilling, and M. H. Saier Jr. Catabolite repression and activation in Bacillus subtilis : Dependency on CcpA, HPr, and HprK. Journal of Bacteriology, 187(22):7826–7839, 2005.CrossRefGoogle Scholar
  15. [LK05]
    W. Li and H. Kurata. A grid layout algorithm for automatic drawing of biochemical networks. Bioinformatics, 21(9):2036–2042, 2005.CrossRefGoogle Scholar
  16. [MNON04]
    Y. Makita, M. Nakao, N. Ogasawara, and K. Nakai. DBTBS: database of transcriptional regulation in Bacillus subtilis and its contribution to comparative genomics. Nucleic Acids Research, 32:D75–77, 2004.CrossRefGoogle Scholar
  17. [MSM+01]
    M. S. Moreno, B. L. Schneider, R. R. Maile, W. Weyler, and M. H. Saier Jr. Catabolite repression mediated by the CcpA protein in Bacillus sub-tilis : Novel modes of regulation by whole-genome analysis. Molecular Biology, 39(5):1366–1381, 2001.Google Scholar
  18. [SH00]
    J. Stulke and W. Hillen. Regulation of carbon catabolism in bacillus species. Annual Review of Microbiology, 54:849–880, 2000.CrossRefGoogle Scholar
  19. [SLN05]
    P. Saraiya, P. Lee, and C. North. Visualization of graphs with associated timeseries data. In Proc. IEEE Symp. Information Visualization (InfoVis’05), pages 225-232, 2005.Google Scholar
  20. [SMO+03]
    P. Shannon, A. Markiel, O. Ozier, N. S. Baliga, J. T. Wang, D. Ramage, N. Amin, B. Schwikowski, and T. Ideker. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Research, 13(11):2498–2504, 2003.CrossRefGoogle Scholar
  21. [The00]
    The Gene Ontology Consortium. Gene ontology: Tool for the unification of biology. Nature Genetics, 25:25–29, 2000.CrossRefGoogle Scholar
  22. [War04]
    C. Ware. Information Visualization: Perception for Design. Morgan Kaufmann Publishers, 2nd edition, 2004.Google Scholar
  23. [WL03]
    J. B. Warner and J. S. Lolkema. CcpA-dependent carbon catabolite repression in bacteria. Microbiology and Molecular Biology Reviews, 67(4):475–490, 2003.CrossRefGoogle Scholar

Copyright information

© Springer 2008

Authors and Affiliations

  • Michel A. Westenberg
    • 1
  • Sacha A. F. T. van Hijum
    • 2
  • Andrzej T. Lulko
    • 2
  • Oscar P. Kuipers
    • 2
  • Jos B. T. M. Roerdink
    • 1
  1. 1.Institute for Mathematics and Computing ScienceUniversity of GroningenAV GroningenThe Netherlands
  2. 2.Department of Genetics, Groningen Biomolecular Sciences and Biotechnology InstituteUniversity of GroningenAA HarenThe Netherlands

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