DISBi: A Flexible Framework for Integrating Systems Biology Data

  • Rüdiger BuscheEmail author
  • Henning Dannheim
  • Dietmar Schomburg
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11371)


Systems biology aims at understanding an organism in its entirety. This objective can only be achieved with the joint effort of specialized work groups. These collaborating groups need a centralized platform for data exchange. Instead data is often uncoordinatedly managed using heterogeneous data formats. Such circumstances present a major hindrance to gaining a global understanding of the data and to automating analysis routines.

DISBi is a framework for creating an integrated online environment that solves these problems. It enables researchers to filter, integrate and analyze data directly in the browser. A DISBi application dynamically adapts to its data model. Thus DISBi offers a solution for a wide range of systems biology projects.

An example installation is available at Source code and documentation are available from


Systems biology Data integration Data exchange 



The authors thank Meina Neumann-Schaal for critical reading of the manuscript and four anonymous reviewer for their instructive comments. Rüdiger Busche thanks Pascal Nieters for support in the publication process.

This work was supported by the Federal State of Lower Saxony, Niedersächsisches Vorab (VWZN2889)/3215.


  1. 1.
    Bauch, A., et al.: openBIS: a flexible framework for managing and analyzing complex data in biology research. BMC Bioinform. 12(1), 468 (2011). Scholar
  2. 2.
    Bugacov, A., Czajkowski, K., Kesselman, C., Kumar, A., Schuler, R.E., Tangmunarunkit, H.: Experiences with DERIVA: an asset management platform for accelerating eScience. In: Proceedings of the 13th IEEE International Conference on eScience, eScience 2017, pp. 79–88 (2017).
  3. 3.
    Fuchs, S., et al.: Aureolib - a proteome signature library: towards an understanding of staphylococcus aureus pathophysiology. PLoS One 8(8), e70669 (2013). Scholar
  4. 4.
    Hunter, J.D.: Matplotlib: a 2D graphics environment. Comput. Sci. Eng. 9(3), 99–104 (2007). Scholar
  5. 5.
    Jones, E., Oliphant, T., Peterson, P.: SciPy: open source scientific tools for Python (2014)Google Scholar
  6. 6.
    Kitano, H.: Systems biology: a brief overview. Science 295(5560), 1662–1664 (2002). Scholar
  7. 7.
    Lubitz, T., Hahn, J., Bergmann, F.T., Noor, E., Klipp, E., Liebermeister, W.: SBtab: a flexible table format for data exchange in systems biology. Bioinformatics 32(16), 2559–2561 (2016). Scholar
  8. 8.
    Rocca-Serra, P., et al.: ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level. Bioinformatics 27, 2354–2356 (2011). Scholar
  9. 9.
    Schuler, R.E., Kesselman, C., Czajkowski, K.: Accelerating data-driven discovery with scientific asset management. In: 2016 IEEE 12th International Conference on e-Science (e-Science), pp. 31–40. IEEE (2016).
  10. 10.
    Taylor, C.F., et al.: Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat. Biotechnol. 26(8), 889–896 (2008). Scholar
  11. 11.
    Van Der Walt, S., Colbert, S.C., Varoquaux, G.: The NumPy array: a structure for efficient numerical computation. Comput. Sci. Eng. 13(2), 22–30 (2011). Scholar
  12. 12.
    Wolf, J., et al.: A systems biology approach reveals major metabolic changes in the thermoacidophilic archaeon Sulfolobus solfataricus in response to the carbon source L-fucose versus D-glucose. Mol. Microbiol. 102(5), 882–908 (2016). Scholar
  13. 13.
    Wolstencroft, K., et al.: The SEEK: a platform for sharing data and models in systems biology. Methods Enzymol. 500, 629–655 (2011). Scholar
  14. 14.
    Wruck, W., Peuker, M., Regenbrecht, C.R.A.: Data management strategies for multinational large-scale systems biology projects. Brief. Bioinform. 15(1), 65–78 (2014). Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Institute of Cognitive ScienceOsnabrück UniversityOsnabrückGermany
  2. 2.Department for Bioinformatics and BiochemistryTechnische Universität BraunschweigBraunschweigGermany

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