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. 2019 Oct 8;20:202. doi: 10.1186/s13059-019-1811-3

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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. 1 — Overall performance of 36 miRNA-disease association predictors on the benchmarking datasets. a The flow chart depicting the inclusion/exclusion criterion for the predictors. The count of predictors included/excluded at each step is indicated by the number in the parentheses, and the fractions of predictors trained with different training datasets are depicted by the associated pie charts. b Precision-recall curves of the top ten predictors in terms of AUPRC on the ALL benchmarking dataset. c The statistics of correctly predicted miRNA-disease association pairs among the top 100, top 500, top 1000, and top 5% highly scored predictions on the ALL benchmarking dataset. d Precision-recall curves of the top ten predictors in terms of AUPRC on the CAUSAL benchmarking dataset