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Random Walk With Restart on Multiplex and Heterogeneous Biological Networks

Alberto Valdeolivas, Laurent Tichit, Claire Navarro, Sophie Perrin, Gaëlle Odelin, Nicolas Levy, Pierre Cau, Elisabeth Remy, Anaïs Baudot
doi: https://doi.org/10.1101/134734
Alberto Valdeolivas
1Aix-Marseille Université, CNRS, Centrale Marseille, I2M UMR 7373, Marseille, France.
2ProGeLife, 8 Rue Sainte Barbe 13001, Marseille, France.
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Laurent Tichit
1Aix-Marseille Université, CNRS, Centrale Marseille, I2M UMR 7373, Marseille, France.
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Claire Navarro
3Aix-Marseille Université, INSERM, UMR S910, Faculté de Médecine, France.
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Sophie Perrin
3Aix-Marseille Université, INSERM, UMR S910, Faculté de Médecine, France.
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Gaëlle Odelin
2ProGeLife, 8 Rue Sainte Barbe 13001, Marseille, France.
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Nicolas Levy
3Aix-Marseille Université, INSERM, UMR S910, Faculté de Médecine, France.
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Pierre Cau
2ProGeLife, 8 Rue Sainte Barbe 13001, Marseille, France.
3Aix-Marseille Université, INSERM, UMR S910, Faculté de Médecine, France.
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Elisabeth Remy
1Aix-Marseille Université, CNRS, Centrale Marseille, I2M UMR 7373, Marseille, France.
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Anaïs Baudot
1Aix-Marseille Université, CNRS, Centrale Marseille, I2M UMR 7373, Marseille, France.
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ABSTRACT

Recent years have witnessed an exponential growth in the number of identified interactions between biological molecules. These interactions are usually represented as large and complex networks, calling for the development of appropriated tools to exploit the functional information they contain. Random walk with restart is the state-of-the-art guilt-by-association approach. It explores the network vicinity of gene/protein seeds to study their functions, based on the premise that nodes related to similar functions tend to lie close to each others in the networks.

In the present study, we extended the random walk with restart algorithm to multiplex and heterogeneous networks. The walk can now explore different layers of physical and functional interactions between genes and proteins, such as protein-protein interactions and co-expression associations. In addition, the walk can also jump to a network containing different sets of edges and nodes, such as phenotype similarities between diseases.

We devised a leave-one-out cross-validation strategy to evaluate the algorithms abilities to predict disease-associated genes. We demonstrate the increased performances of the multiplex-heterogeneous random walk with restart as compared to several random walks on monoplex or heterogeneous networks. Overall, our framework is able to leverage the different interaction sources to outperform current approaches.

Finally, we applied the algorithm to predict genes candidate for being involved in the Wiedemann-Rautenstrauch syndrome, and to explore the network vicinity of the SHORT syndrome.

The source code and the software are freely available at: https://github.com/alberto-valdeolivas/RWR-MH.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted August 30, 2017.
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Random Walk With Restart on Multiplex and Heterogeneous Biological Networks
Alberto Valdeolivas, Laurent Tichit, Claire Navarro, Sophie Perrin, Gaëlle Odelin, Nicolas Levy, Pierre Cau, Elisabeth Remy, Anaïs Baudot
bioRxiv 134734; doi: https://doi.org/10.1101/134734
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Random Walk With Restart on Multiplex and Heterogeneous Biological Networks
Alberto Valdeolivas, Laurent Tichit, Claire Navarro, Sophie Perrin, Gaëlle Odelin, Nicolas Levy, Pierre Cau, Elisabeth Remy, Anaïs Baudot
bioRxiv 134734; doi: https://doi.org/10.1101/134734

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