ApiNATOMY: Towards Multiscale Views of Human Anatomy

  • Bernard de Bono
  • Pierre Grenon
  • Michiel Helvensteijn
  • Joost Kok
  • Natallia Kokash
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8819)

Abstract

Physiology experts deal with complex biophysical relationships, across multiple spatial and temporal scales. Automating the discovery of such relationships, in terms of physiological meaning, is a key goal to the physiology community. ApiNATOMY is an effort to provide an interface between the physiology expert’s knowledge and all ranges of data relevant to physiology. It does this through an intuitive graphical interface for managing semantic metadata and ontologies relevant to physiology. In this paper, we present a web-based ApiNATOMY environment, allowing physiology experts to navigate through circuitboard visualizations of body components, and their cardiovascular and neural connections, across different scales. Overlaid on these schematics are graphical renderings of organs, neurons and gene products, as well as mathematical models of processes semantically annotated with this knowledge.

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References

  1. 1.
    de Bono, B., Hoehndorf, R., Wimalaratne, S., Gkoutos, G., Grenon, P.: The RICORDO approach to semantic interoperability for biomedical data and models: strategy, standards and solutions. BMC Research Notes 4, 313 (2011)CrossRefGoogle Scholar
  2. 2.
    Katifori, A., Halatsis, C., Lepouras, G., Vassilakis, C., Giannopoulou, E.: Ontology visualization methods - a survey. ACM Comput. Surv. 39(4) (2007)Google Scholar
  3. 3.
    Blake, J.A., et al.: Gene ontology annotations and resources. Nucleic Acids Res. 535, D530–D535 (2013)Google Scholar
  4. 4.
    Hastings, J., de Matos, P., Dekker, A., Ennis, M., Harsha, B., Kale, N., Muthukrishnan, V., Owen, G., Turner, S., Williams, M., Steinbeck, C.: The ChEBI reference database and ontology for biologically relevant chemistry: enhancements for 2013. Nucleic Acids Res. 41(D1), D456–D463 (2013)Google Scholar
  5. 5.
    Bard, J., Rhee, S.Y., Ashburner, M.: An ontology for cell types. Genome Biol. 6(2), R21 (2005)Google Scholar
  6. 6.
    Rosse, C., Mejino Jr., J.L.V.: A reference ontology for biomedical informatics: the foundational model of anatomy. J. Biomed. Inform. 36(6), 478–500 (2003)CrossRefGoogle Scholar
  7. 7.
    EBI: Arrayexpress home, EBI (2012), http://www.ebi.ac.uk/arrayexpress/
  8. 8.
    Harnisch, L., Matthews, I., Chard, J., Karlsson, M.O.: Drug and disease model resources: a consortium to create standards and tools to enhance model-based drug development. CPT Pharmacomet. Syst. Pharmacol. 2, e34 (2013)Google Scholar
  9. 9.
    de Bono, B., Grenon, P., Sammut, S.: ApiNATOMY: A novel toolkit for visualizing multiscale anatomy schematics with phenotype-related information. Hum. Mutat. 33(5), 837–848 (2012)CrossRefGoogle Scholar
  10. 10.
    Kokash, N., de Bono, B.J.K.: Template-based treemaps to preserve spatial constraints. In: Proc. IVAPP 2014 (2014)Google Scholar
  11. 11.
    de Bono, B.: Achieving semantic interoperability between physiology models and clinical data. In: Proc. of IEEE Int. Conf. on e-Science Workshops, pp. 135–142 (2011)Google Scholar
  12. 12.
    Gardner, D., et al.: The neuroscience information framework: A data and knowledge environment for neuroscience. Neuroinformatics 6(3), 149–160 (2008)CrossRefGoogle Scholar
  13. 13.
    Mitsuhashi, N., Fujieda, K., Tamura, T., Kawamoto, S., Takagi, T., Okubo, K.: Bodyparts3d: 3d structure database for anatomical concepts. Nucleic Acids Res. 37, D782–D785 (2009)Google Scholar
  14. 14.
    Ascoli, G.A.: Mobilizing the base of neuroscience data: the case of neuronal morphologies. Nat. Rev. Neurosci. 7(4), 318–324 (2006)CrossRefGoogle Scholar
  15. 15.
    Johnson, B., Shneiderman, B.: Tree-maps: a space-filling approach to the visualization of hierarchical information structures. In: Proc. of the 2nd Conference on Visualization 1991, pp. 284–291. IEEE (1991)Google Scholar
  16. 16.
    Blanch, R., Lecolinet, E.: Browsing zoomable treemaps: Structure-aware multi-scale navigation techniques. TVCG 13, 1248–1253 (2007)Google Scholar
  17. 17.
    Holten, D.: Hierarchical edge bundles: Visualization of adjacency relations in hierarchical data. IEEE Transactions on Visualization and Computer Graphics 12(5), 741–748 (2006)CrossRefGoogle Scholar
  18. 18.
    Gansner, E.R., Hu, Y., North, S.C., Scheidegger, C.E.: Multilevel agglomerative edge bundling for visualizing large graphs. In: Battista, G.D., Fekete, J.D., Qu, H. (eds.) Proce. of PacificVis, pp. 187–194. IEEE Computer Society (2011)Google Scholar
  19. 19.
    Hurter, C., Ersoy, O., Telea, A.: Graph bundling by kernel density estimation. Comp. Graph. Forum 31, 865–874 (2012)CrossRefGoogle Scholar
  20. 20.
    Fruchterman, T., Reingold, E.: Graph drawing by force-directed placement. Software Practice and Experience 21(11), 1129–1164 (1991)CrossRefGoogle Scholar
  21. 21.
    Bostock, M.: Sticky force layout. Online visualization tool, http://bl.ocks.org/mbostock/3750558 (accessed on May 20, 2014)
  22. 22.
    EBI: Ensemble. Online web page (2014) (accessed on May 20, 2014)Google Scholar
  23. 23.
    Weaver, C., Bruns, C., Helvensteijn, M.: SharkViewer. Howard Hughes Medical Institute, Janelia Farm Research Campus. doi:10.5281/zenodo.10053 (2014)Google Scholar
  24. 24.
    Magnenat-Thalmann, N., Ratib, O., Choi, H.F. (eds.): 3D Multiscale Physiological Human. Springer (2014)Google Scholar
  25. 25.
    Magnenat-Thalmann, N. (ed.): 3DPH 2009. LNCS, vol. 5903. Springer, Heidelberg (2009)Google Scholar
  26. 26.
    Burger, A., Davidson, D., Baldock, R. (eds.): Anatomy Ontologies for Bioinformatics. Computational Biology, vol. 6. Springer (2008)Google Scholar
  27. 27.
    Burch, M., Diehl, S.: Trees in a treemap: Visualizing multiple hierarchies. In: Proc. VDA 2006 (2006)Google Scholar
  28. 28.
    Battista, G.D., Eades, P., Tamassia, R., Tollis, I.G.: Graph Drawing: Algorithms for the Visualization of Graphs. Prentice Hall (1999)Google Scholar
  29. 29.
    Holten, D., van Wijk, J.J.: Force-directed edge bundling for graph visualization. Comput. Graph. Forum 28(3), 983–990 (2009)CrossRefGoogle Scholar
  30. 30.
    Selassie, D., Heller, B., Heer, J.: Divided edge bundling for directional network data. IEEE Trans. Visualization & Comp. Graphics (Proc. InfoVis) (2011)Google Scholar
  31. 31.
    Hunter, P., et al.: A vision and strategy for the virtual physiological human in 2010 and beyond. Philos. Trans. A Math. Phys. Eng. Sci. 368(2010), 2595–2614 (1920)Google Scholar
  32. 32.
    Wikipedia: Zygote body (2014), http://en.wikipedia.org/wiki/Zygote_Body (accessed on May 20, 2014)
  33. 33.
    de Bono, B., Hunter, P.: Integrating knowledge representation and quantitative modelling in physiology. Biotechnol. J. 7(8), 958–972 (2012)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Bernard de Bono
    • 1
  • Pierre Grenon
    • 1
  • Michiel Helvensteijn
    • 2
  • Joost Kok
    • 2
  • Natallia Kokash
    • 2
  1. 1.University College London (UCL)United Kingdom
  2. 2.Leiden Institute of Advanced Computer Science (LIACS)The Netherlands

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