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. 2019 Mar 12;9:4267. doi: 10.1038/s41598-019-38498-7

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© The Author(s) 2019

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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(a) Correlation between InterPep global score and prediction quality measured as Matthew’s Correlation Coefficient between the local score and native contacts, for different ways of combining the cluster score and highest local score. The weight for the local score is k and cluster score 1 − k. Optimal weight is found at k = 0.39. (b) Distribution of precision of predictions for different InterPep score cutoff values.