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. 2022 Nov 19;12:19906. doi: 10.1038/s41598-022-23775-9

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© The Author(s) 2022

Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

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(a) Flow chart of our investigation: The outputs of a healthy and a defect (disease) network (receiving the same input vector) are compared. Depending on their difference they are assigned to a specific class: Class A, if both outputs are equal (no disease), class B, if the disease network has a lower but non-zero output (symptomatic disease), class C, if the disease network has zero output, while the healthy network has a non-zero output (lethal disease), class D, if both the healthy and the disease network have zero output. (b) Definition of node states and visual representation of the effect of a non-functional node. (c) Illustration of branching and visual representation of compensating a defect via interacting pathways. (d) Schematic representation of the full model and illustration of the layer structure.