Multiscale Scatterplot Matrix for Visual and Interactive Exploration of Metabonomic Data

  • Fabien Jourdan
  • Alain Paris
  • Pierre-Yves Koenig
  • Guy Melançon
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4370)


We describe a method turning scatterplot matrix visualizations into malleable graphical objects facilitating interaction and selection of pixelized data elements. The method relies on density estimation techniques [1,2] applied through standard image processing. A 2D scatterplot is considered as an image and is then transformed into nested regions that can be easily selected. Based on Wattenberg and Fisher [3], and as confirmed by our experience, we believe users have a good intuition interpreting and interacting with these multiscale graphical objects. Bio-molecular data serves here as a case study for our methodology. The method was discussed and designed in collaboration with experts in metabonomics and has proven to be useful and complementary to classical statistical methods.


Information Visualization Visual Exploration Graphical Object Drug Taking Molecule Concentration 
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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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Fabien Jourdan
    • 1
  • Alain Paris
    • 1
  • Pierre-Yves Koenig
    • 2
  • Guy Melançon
    • 2
  1. 1.UMR1089 Xénobiotiques INRA-ENVT, Institut National de Recherche AgronomiqueFrance
  2. 2.Laboratoire d’Informatique, de Robotique et de Micro-électronique de Montpellier, LIRMM UMR CNRS 5506France

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