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. 2021 Oct 25;22:520. doi: 10.1186/s12859-021-04439-3

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© The Author(s) 2021

Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

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Fig. 4 — Cancer-related validation of the novel aging-related gene predictions for the eight considered (sub)networks, each under its best predictive model, when using the primary GenAge-based definition of aging- and non-aging-related gene labels, and when using HPRD. On the x-axis, the number in the parentheses after the name of each (sub)network is the number of the novel predictions. The precision score of a (sub)network is the percentage of novel predictions that are validated by the cancer-related data. Note again that we have two groups of results for wNetWalk-Dynamic, i.e., wNetWalk-Dynamic Existing and wNetWalk-Dynamic Proposed, which we already explained in the caption of Fig. 2. For results when using BioGRID instead of HPRD, see Additional file 1: Fig. S7