The Landscape Metaphor for Visualization of Molecular Similarities

The Landscape Metaphor for Visualization of Molecular Similarities

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.

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Authors
  • Kriege, Nils M.
  • Mutzel, Petra
  • Gronemann, Martin
  • Jünger, Michael
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Shortfacts
Category
Paper in Conference Proceedings or in Workshop Proceedings (Paper)
Event Title
8th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP)
Divisions
Data Mining and Machine Learning
Event Location
Barcelona, Spain
Event Type
Conference
Event Dates
21.-24.02.2013
Series Name
Computer Vision, Imaging and Computer Graphics - Theory and Applications
ISSN/ISBN
978-3-662-44910-3
Publisher
Springer
Page Range
pp. 85-100
Date
2014
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