Abstract
Molecular biology produces and accumulates huge amounts of data that are generally integrated within graphs of molecules linked by various interactions. Exploring potentially interesting substructures (clusters, motifs) within such graphs requires proper abstraction and visualization methods. Most layout techniques (edge and nodes spatial organization) prove insufficient in this case. Royer et al. introduced in 2008 Power graph analysis, a dedicated program using classes of nodes with similar properties and classes of edges linking node classes to achieve a lossless graph compression. The contributions of this paper are twofold. First, we formulate and study this issue in the framework of Formal Concept Analysis. This leads to a generalized view of the initial problem offering new variants and solving approaches. Second, we state the FCA modeling problem in a logical setting, Answer Set programming, which provides a great flexibility for the specification of concept search spaces.
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Notes
- 1.
Repository at http://powergrasp.bourneuf.net.
- 2.
powergrasp/tests/.
- 3.
powergrasp/ASPSources/postprocessing.lp.
- 4.
powergrasp/ASPSources/findbestorientedbiclique.lp.
- 5.
powergrasp/ASPSources/by_priority.lp.
- 6.
powergrasp/ASPSources/by_fuzzy_priority.lp.
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Acknowledgments
We wish to thank D. Tagu (INRA Le Rheu) and N. Théret (Inserm) for providing us the networks used in the results section. We would also like to express our gratitude to the reviewers for their feedbacks.
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Bourneuf, L., Nicolas, J. (2017). FCA in a Logical Programming Setting for Visualization-Oriented Graph Compression. In: Bertet, K., Borchmann, D., Cellier, P., Ferré, S. (eds) Formal Concept Analysis. ICFCA 2017. Lecture Notes in Computer Science(), vol 10308. Springer, Cham. https://doi.org/10.1007/978-3-319-59271-8_6
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