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. 2016 Oct 6;17(Suppl 13):351. doi: 10.1186/s12859-016-1224-1

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© The Author(s) 2016

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Fig. 2 — Discriminative power of subnetwork markers across independent gene expression datasets. The markers were identified and ranked on GSE2034 and their discriminative power was evaluated on NKI295. We computed the mean absolute t-score of the top K=10, 20, 30, 40, and 50 markers by different methods for the following PPI datasets: a Chuang, b HPRD, c GASOLINE, and d BioGRID