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. 2023 Feb 2;4(2):181–202. doi: 10.1038/s43018-022-00510-x

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Extended Data Fig. 5 — a, Bar plot showing the probability of correctly identifying upregulated or downregulated kinases by the analysis of the ‘top-10-hit’ using the indicated inference methods (n = 103 kinase perturbations). b, Bar plot of the differential rank (Δ-rank) of activity between SPHINKS and the indicated inference methods for the kinases significantly active in each GBM subtype by SPHINKS and common to the networks of all five approaches (n = 85 GBM samples). Kinases are ordered according to the rank of activity by SPHINKS.