Skip to main content
SpringerLink
Log in
Book cover

International Conference on Computer Vision, Imaging and Computer Graphics

VISIGRAPP 2013: Computer Vision, Imaging and Computer Graphics -- Theory and Applications pp 85–100Cite as

The Landscape Metaphor for Visualization of Molecular Similarities

  • Conference paper
  • First Online:

  • 754 Accesses

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 458))

Abstract

Clustered graphs are a versatile representation formalism for expressing relations between entities, and simultaneously, reflecting their hierarchical structure. This makes clustered graphs well-suited to model complex structured data. However, obtaining appealing drawings of clustered graphs is a challenging task. We employ the landscape metaphor to visualize clustered graphs in a cheminformatics application. In order to browse chemical compound libraries in a systematic way, we consider two different molecular similarity concepts. Combining the scaffold-based cluster hierarchy with molecular similarity graphs allows for new insights in the analysis of large molecule libraries. Here, like in certain other application domains, the cluster hierarchy does not necessarily reflect the underlying graph structure. We improve the approach taken in [1] by applying a modified treemap algorithm for node positioning that takes the edges of the graph into account. Experiments with real-world instances clearly show that the new algorithm leads to significant improvements in terms of the edge lengths.

Research supported by the German Research Foundation (DFG), priority programme “Algorithm Engineering” (SPP 1307).

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    http://jung.sourceforge.net

  2. 2.

    Graph Drawing E-Print Archive, http://gdea.informatik.uni-koeln.de/.

  3. 3.

    Available from PubChem BioAssay, AID 361.

  4. 4.

    Machine with Core i7 2.7 GHz and 8 GB RAM.

References

  1. Gronemann, M., Jünger, M.: Drawing clustered graphs as topographic maps. In: Didimo, W., Patrignani, M. (eds.) GD 2012. LNCS, vol. 7704, pp. 426–438. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  2. Brown, N.: Chemoinformatics - an introduction for computer scientists. ACM Comput. Surv. 41, 1–38 (2009)

    Article  Google Scholar 

  3. Herhaus, C., Karch, O., Bremm, S., Rippmann, F.: MolWind - mapping molecule spaces to geospatial worlds. Chem. Cent. J. 3, P32 (2009)

    Article  Google Scholar 

  4. Klein, K., Kriege, N., Mutzel, P.: Scaffold hunter: facilitating drug discovery by visual analysis of chemical space. In: Csurka, G., Kraus, M., Laramee, R.S., Richard, P., Braz, J. (eds.) VISIGRAPP 2012. CCIS, vol. 359, pp. 176–192. Springer, Heidelberg (2013)

    Google Scholar 

  5. Lounkine, E., Wawer, M., Wassermann, A.M., Bajorath, J.: SARANEA: a freely available program to mine structure-activity and structure-selectivity relationship information in compound data sets. J. Chem. Inf. Model. 50, 68–78 (2010)

    Article  Google Scholar 

  6. Strobelt, H., Bertini, E., Braun, J., Deussen, O., Groth, U., Mayer, T.U., Merhof, D.: HiTSEE KNIME: a visualization tool for hit selection and analysis in high-throughput screening experiments for the KNIME platform. BMC Bioinform. 13(suppl. 8), S4 (2012)

    Article  Google Scholar 

  7. Wetzel, S., Klein, K., Renner, S., Rauh, D., Oprea, T.I., Mutzel, P., Waldmann, H.: Interactive exploration of chemical space with Scaffold Hunter. Nat. Chem. Biol. 5, 581–583 (2009)

    Article  Google Scholar 

  8. Irwin, J.J.: Staring off into chemical space. Nat. Chem. Biol. 5, 536–537 (2009)

    Article  Google Scholar 

  9. Wawer, M., Peltason, L., Weskamp, N., Teckentrup, A., Bajorath, J.: Structure-activity relationship anatomy by network-like similarity graphs and local structure-activity relationship indices. J. Med. Chem. 51, 6075–6084 (2008)

    Article  Google Scholar 

  10. Fruchterman, T.M.J., Reingold, E.M.: Graph drawing by force-directed placement. Softw. Pract. Exper. 21, 1129–1164 (1991)

    Article  Google Scholar 

  11. Schuffenhauer, A., Varin, T.: Rule-based classification of chemical structures by scaffold. Mol. Inform. 30, 646–664 (2011)

    Google Scholar 

  12. Schuffenhauer, A., Ertl, P., Roggo, S., Wetzel, S., Koch, M.A., Waldmann, H.: The scaffold tree - visualization of the scaffold universe by hierarchical scaffold classification. J. Chem. Inf. Model. 47, 47–58 (2007)

    Article  Google Scholar 

  13. Guha, R.: The ups and downs of structure-activity landscapes. In: Bajorath, J. (ed.) Chemoinformatics and Computational Chemical Biology. Methods in Molecular Biology, vol. 672, pp. 101–117. Humana Press (2011)

    Google Scholar 

  14. Peltason, L., Iyer, P., Bajorath, J.: Rationalizing three-dimensional activity landscapes and the influence of molecular representations on landscape topology and the formation of activity cliffs. J. Chem. Inf. Model. 50, 1021–1033 (2010)

    Article  Google Scholar 

  15. Sugiyama, K., Misue, K.: Visualization of structural information: Automatic drawing of compound digraphs. IEEE Trans. SMC 21, 876–892 (1991)

    MathSciNet  Google Scholar 

  16. Huang, M.L., Eades, P.: A fully animated interactive system for clustering and navigating huge graphs. In: Whitesides, S.H. (ed.) GD 1998. LNCS, vol. 1547, pp. 374–383. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  17. Gansner, E.R., Hu, Y., Kobourov, S.G., Volinsky, C.: Putting recommendations on the map: visualizing clusters and relations. In: Proceedings of the ACM Conference on Recommender Systems, pp. 345–348 (2009)

    Google Scholar 

  18. Gansner, E.R., Hu, Y., Kobourov, S.G.: GMap: Visualizing graphs and clusters as maps. In: Pacific Visualization Symposium (PacificVis), pp. 201–208. IEEE (2010)

    Google Scholar 

  19. Fabrikant, S.I., Montello, D.R., Mark, D.M.: The natural landscape metaphor in information visualization: The role of commonsense geomorphology. J. Am. Soc. Inf. Sci. Technol. 61, 253–270 (2010)

    Google Scholar 

  20. Johnson, B., Shneiderman, B.: Tree-maps: a space-filling approach to the visualization of hierarchical information structures. In: Proceedings of the 2nd Conference on Visualization, pp. 284–291 (1991)

    Google Scholar 

  21. Schulz, H.J.: Treevis.net: A tree visualization reference. IEEE Comput. Graphics Appl. 31, 11–15 (2011)

    Article  Google Scholar 

  22. Maggiora, G.M., Shanmugasundaram, V.: Molecular similarity measures. Methods Mol. Biol. 672, 39–100 (2011)

    Article  Google Scholar 

  23. Steinbeck, C., Hoppe, C., Kuhn, S., Floris, M., Guha, R., Willighagen, E.L.: Recent developments of the chemistry development kit (CDK) - an open-source java library for chemo- and bioinformatics. Curr. Pharm. Des. 12, 2111–2120 (2006)

    Article  Google Scholar 

  24. Bon, R.S., Waldmann, H.: Bioactivity-guided navigation of chemical space. Acc. Chem. Res. 43, 1103–1114 (2010)

    Article  Google Scholar 

  25. Girvan, M., Newman, M.E.J.: Community structure in social and biological networks. Proc. Natl. Acad. of Sci. 99, 7821–7826 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  26. de Berg, M., Onak, K., Sidiropoulos, A.: Fat polygonal partitions with applications to visualization and embeddings. CoRR abs/1009.1866 (2010)

    Google Scholar 

Download references

Acknowledgements

We would like to thank Claude Ostermann and Philipp Thiel for their valuable feedback and for sharing their chemical knowledge.

Author information

Authors and Affiliations

  1. Institut für Informatik, Universität zu Köln, Cologne, Germany

    Martin Gronemann & Michael Jünger

  2. Department of Computer Science, Technische Universität Dortmund, Dortmund, Germany

    Nils Kriege & Petra Mutzel

Authors
  1. Martin Gronemann
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michael Jünger
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nils Kriege
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Petra Mutzel
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Martin Gronemann .

Editor information

Editors and Affiliations

  1. Università di Catania, Catania, Catania, Italy

    Sebastiano Battiato

  2. Inria/ZIRST, Saint Ismier, France

    Sabine Coquillart

  3. Swansea University, Swansea, United Kingdom

    Robert S. Laramee

  4. Linnaeus University, Växjö, Sweden

    Andreas Kerren

  5. Escola Superior de Tecnologia do IPS, Setúbal, Portugal

    José Braz

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Gronemann, M., Jünger, M., Kriege, N., Mutzel, P. (2014). The Landscape Metaphor for Visualization of Molecular Similarities. In: Battiato, S., Coquillart, S., Laramee, R., Kerren, A., Braz, J. (eds) Computer Vision, Imaging and Computer Graphics -- Theory and Applications. VISIGRAPP 2013. Communications in Computer and Information Science, vol 458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44911-0_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-44911-0_6

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-44910-3

  • Online ISBN: 978-3-662-44911-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation