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References
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1. Bersanelli, M. et al. (2016). Network diffusion-based analysis of high-throughput data for the detection of differentially enriched modules. Scientific Reports. (6), 34841.
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2. Harchaoui, Z., et al. (2013). Kernel-based methods for hypothesis testing: a unified view. IEEE Signal Processing Magazine. (30), 87–97.
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3. Mostafavi, S., et al. (2008). Genemania: a real-time multiple association network integration algorithm for predicting gene function.Genome Biology. (9), S4.
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1. Bersanelli, M. et al. (2016). Network diffusion-based analysis of high-throughput data for the detection of
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differentially enriched modules. Scientific Reports. (6), 34841.
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2. Harchaoui, Z., et al. (2013). Kernel-based methods for hypothesis testing: a unified view. IEEE Signal Processing
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Magazine. (30), 87–97.
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3. Mostafavi, S., et al. (2008). Genemania: a real-time multiple association network integration algorithm for
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predicting gene function.Genome Biology. (9), S4.
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4. Tsuda, K., et al. (2005). Fast protein classification with multiple networks. Bioinformatics, (21), 59–65.
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5. Vandin, F., et al. (2010). Algorithms for detecting significantly mutated pathways in cancer. Lecture Notes in Computer Science. 6044, 506–521.
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5. Vandin, F., et al. (2010). Algorithms for detecting significantly mutated pathways in cancer. Lecture Notes in
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Computer Science. 6044, 506–521.
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