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. 2015 Sep 8;5:13786. doi: 10.1038/srep13786

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Copyright © 2015, Macmillan Publishers Limited

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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The best obtained layout (η = 3.1%) by our hierarchical visualization technique of the human diseasome is shown by circles of radiuses σ_i in (a) and by a traditional graph in (b). The nodes represent diseases, colored according to known disease categories⁶⁴, while the σ_i width of the distributions in (a) indicates the uncertainty of the positions. In the numerical optimization for this network we primarily focused on the positioning of the nodes, thus the optimization for the widths and normalizations was only turned on as a fine-tuning after an initial layout was obtained.