Multiscale scatterplot matrix for visual and interactive exploration of metabonomics data

Abstract : 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, 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.
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Communication dans un congrès
Pierre Levy, François Poulet. Visual Information Expert Workshop, Apr 2006, Paris, France, Springer, pp.202-215, 2006, Lecture Notes in Computer Science. 〈http://www.springerlink.com/content/816k351w661t8359/〉. 〈10.1007/978-3-540-71027-1_18〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00091360
Contributeur : Guy Melançon <>
Soumis le : mercredi 6 septembre 2006 - 09:46:46
Dernière modification le : samedi 15 septembre 2018 - 01:07:49
Document(s) archivé(s) le : jeudi 20 septembre 2012 - 10:20:16

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Guy Melançon, Fabien Jourdan, Alain Paris, Pierre-Yves Koenig. Multiscale scatterplot matrix for visual and interactive exploration of metabonomics data. Pierre Levy, François Poulet. Visual Information Expert Workshop, Apr 2006, Paris, France, Springer, pp.202-215, 2006, Lecture Notes in Computer Science. 〈http://www.springerlink.com/content/816k351w661t8359/〉. 〈10.1007/978-3-540-71027-1_18〉. 〈lirmm-00091360〉

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