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Vienna Graph Clustering

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Protein-Protein Interaction Networks

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2074))

Abstract

This paper serves as a user guide to the Vienna graph clustering framework. We review our general memetic algorithm, VieClus, to tackle the graph clustering problem. A key component of our contribution are natural recombine operators that employ ensemble clusterings as well as multi-level techniques. Lastly, we combine these techniques with a scalable communication protocol, producing a system that is able to compute high-quality solutions in a short amount of time. After giving a description of the algorithms employed, we establish the connection of the graph clustering problem to protein–protein interaction networks and moreover give a description on how the software can be used, what file formats are expected, and how this can be used to find functional groups in protein–protein interaction networks.

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Acknowledgements

The research leading to these results has received funding from the European Research Council under the European Community’s Seventh Framework Programme (FP7/2007–2013)/ERC grant agreement No. 340506. The authors acknowledge support by the state of Baden-Württemberg through bwHPC. Parts of this paper has appeared in the proceedings of the 17th Intl. Symp. on Exp. Algorithms [7]; licensed under Creative Commons License CC-BY Leibniz International Proceedings in Informatics Schloss Dagstuhl – Leibniz-Zentrum für Informatik, Dagstuhl Publishing, Germany.

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Correspondence to Christian Schulz .

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Biedermann, S., Henzinger, M., Schulz, C., Schuster, B. (2020). Vienna Graph Clustering. In: Canzar, S., Ringeling, F. (eds) Protein-Protein Interaction Networks. Methods in Molecular Biology, vol 2074. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9873-9_16

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  • DOI: https://doi.org/10.1007/978-1-4939-9873-9_16

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-4939-9872-2

  • Online ISBN: 978-1-4939-9873-9

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