Advertisement

Clinico-Genomic Research Assimilator: A Dicode Use Case

Chapter
Part of the Studies in Big Data book series (SBD, volume 5)

Abstract

Biomedical research becomes increasingly interdisciplinary and collaborative in nature. Researchers need to effectively collaborate and make decisions by meaningfully assembling, mining and analyzing available large-scale volumes of complex multi-faceted data residing in different sources. Through a real scenario, this chapter reports on the practical use of the Dicode solution in the above context. Evaluation results show that the proposed solution enables a meaningful aggregation and analysis of large-scale data in complex biomedical research settings. Moreover, it allows for new working practices that turn the problem of information overload and cognitive complexity into the benefit of knowledge discovery.

Keywords

Genomics Transcriptomics Gene ontology Integration 

References

  1. 1.
    Tsiliki, G., Kossida, S.: Fusion methodologies for biomedical data. J. Proteom. 74, 2774–2785 (2011)CrossRefGoogle Scholar
  2. 2.
    Karacapilidis, N., Tzagarakis, M., Christodoulou, S., Tsiliki, G.: Facilitating and augmenting collaboration in the biomedical domain. Int. J. Syst. Biol. Biomed. Technol. 1(1), 52–65 (2012)Google Scholar
  3. 3.
    Sullivan, D.E., Gabbard, J.J., Shukla, M., Sobral, B.: Data integration for dynamic and sustainable systems biology resources: challenges and lessons learned. Chem. Biodivers. 7(5), 1124–1141 (2010)CrossRefGoogle Scholar
  4. 4.
    Koschmieder, A., Zimmermann, K., Tribl, S., Stoltmann, T., Leser, U.: Tools for managing and analyzing microarray data. Brief Bioinform. 13, 46–60 (2011)Google Scholar
  5. 5.
    Lukk, M., Kapushesky, M., Nikkilä, J., Parkison, H., Goncalves, A., Huber, W., et al.: A global map of human gene expression. Nat. Biotechnol. 28, 322–324 (2010)CrossRefGoogle Scholar
  6. 6.
    Joyce, A.R., Palsson, B.Ø.: The model organism as a system: integrating ‘omics’ data sets. Nat. Rev. Mol. Cell Biol. 7, 198–210 (2006)CrossRefGoogle Scholar
  7. 7.
    Pennisi, E.: Will computers crash genomics? Science 331, 666–668 (2011)CrossRefGoogle Scholar
  8. 8.
    Huttenhower, C., Schroeder, M., Chikina, M.D., Troyanskaya, O.G.: The Sleipnir library for computational functional genomics. Bioinformatics 24(13), 1559–1561 (2008)Google Scholar
  9. 9.
    Baker, M.: Quantitative data: learning to share. Nat. Meth. 9, 39–41 (2012)CrossRefGoogle Scholar
  10. 10.
    Guberman, J.M., Ai, J., Arnaiz, O., Baran, J., Blake, A., Baldock, R. et al.: BioMart central portal: an open database network for the biological community. Database bar041 (2011)Google Scholar
  11. 11.
    Perez-Llamas, C., Gundem, G., Lopez-Bigas, N.: Intregrative Cancer Genomics (IntoGen) in Biomart. Database bar039 (2011)Google Scholar
  12. 12.
    Lee, S.E.: Facilitating collaborative biomedical research. In: Proceedings of GROUP ‘07. Sanibel Island, Chicago, USA (2007)Google Scholar
  13. 13.
    Finholt, T.A.: Collaboratories as a new form of scientific organization. Econ. Innov. New Technol. 12(1), 5–25 (2003)CrossRefGoogle Scholar
  14. 14.
    Spencer, D., Zimmerman, A., Abramson, D.: Special theme: project management in E- Science: challenges and opportunities. Comput. Sup. Coop Work 20, 155–163 (2011)CrossRefGoogle Scholar
  15. 15.
    Atzmueller, M., Puppe, F., Buscher, H.P.: Exploiting background knowledge for knowledge-intensive subgroup discovery. In: Proceedings of IJCAI’05, pp. 647–652 (2005)Google Scholar
  16. 16.
    Huber-Keener, K.J., Liu, X., Wang, Z. et al.: Differential gene expression in Tamoxifen-Resistant breast cancer cells revealed by a new analytical model of RNA-Seq data. PLoS ONE. 7, 7, e41333. DOI= doi: 10.1371/journal.pone.0041333 (2012)
  17. 17.
    Kitchenham, B., Pfleeger, S.L.: Principles of survey research part 5: populations and samples. Softw. Eng. Notes 27(5), 17–20 (2002)CrossRefGoogle Scholar
  18. 18.
    Cugini, J., Damianos, L., Hirschman, L., Kozierok, R., Kurtz, J., Laskowski, S., Scholtz, J.: Methodology for Evaluation of Collaboration Systems, The Evaluation Working Group of The DARPA Intelligent Collaboration and Visualization Program Revision 3.0 (1997)Google Scholar
  19. 19.
    Sun, Y., Greenberg, S.: Places for lightweight group meetings: the design of come together. In Proceedings of GROUP’10, Sanibel Island, Florida, USA, pp. 235–244 (2010)Google Scholar
  20. 20.
    Nielsen, J.: Designing Web Usability: The Practice of Simplicity. New Riders Publishing, Indianapolis (1999)Google Scholar
  21. 21.
    Norman, D.A.: The Design of Everyday Things. The MIT Press, London (1998)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Biomedical Research FoundationAcademy of AthensAthensGreece

Personalised recommendations