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. 2018 Jul 4;50(7):1–7. doi: 10.1038/s12276-018-0110-5

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© The Author(s) 2018

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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Fig. 1 — A Bayesian network learned from the data of childhood asthmatics with a Hill-Climbing algorithm. Edges represent conditional dependencies, and connected nodes represent variables that are conditionally dependent on each other. Red edges represent edges with an arc strength >0.5, blue edges represent edges with an arc strength between 0.2 and 0.5, and black edges represent edges with an arc strength between 0.1 and 0.2. Edges with an arc strength <0.1 were removed from the network. For a certain node, nodes connected above (parent nodes), nodes connected below (children nodes), and the other parent nodes of these children nodes form a Markov blanket, which is required to predict the behavior of that node. Thus, we evaluated the interactive effects of depression severity (parent of the Sx node) and rs4672619 (S16) genotypes (children of the Sx node) on asthma symptom severity (Sx node). A age quartile, Ax anxiety quartile, Dp depression quartile, G gender (male/female), Sx symptom severity quartile, R ethnicity (non-Hispanic white/African American/Hispanic/Asian), and S1-100 top-ranked 100 SNPs (S16, rs4672619)