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. 2019 Jun 24;20:355. doi: 10.1186/s12859-019-2930-2

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© The Author(s). 2019

Open AccessThis 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. 5 — PR curves of RWHN and ten other existing centrality methods. The proteins ranked in top K (cut-off value) by each method (RWHN, DC, IC, SC, BC, CC, NC, PeC, CoEWC, POEM and ION) are selected as candidate essential proteins (positive data set) and the remaining proteins in PPI network are regarded as candidate nonessential proteins (negative data set). With different values of K selected, the values of precision and recall are computed for each method. The values of precision and recall are plotted in PR curves with different cut-off values. a shows the PR curves of RWHN, DC, IC, SC, BC, CC and NC. b shows the PR curves of RWHN and other four methods: CoEWC, PeC, POEM and ION