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. 2017 May 18;17(Suppl 1):55. doi: 10.1186/s12911-017-0449-x

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© The Author(s). 2017

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. 3 — Toy example of Candidate Disease Prioritization. By comparing D _A and D _F, figures show results of candidate disease prioritization by step-by-step. a expresses similarity vector for edges where D _A and D _F are connected to other diseases in PrDN and DrDN. b is a probability of similarity from a through pre-processing. c is KL value that is calculated between two diseases according to formula. KL _A is 0.2 and bigger than KL _F that is near 0. Therefore, intuitive decision for priority is digitized, we can see that same results are appearing. d and e are graphs which express probability distributions for two diseases in b. These graphs display such distribution by order of bigger values. The reason for big difference in KL value is evident by comparing d and e