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. 2022 Jan 21;12:1162. doi: 10.1038/s41598-022-04769-z

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© The Author(s) 2022

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 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) Topological analysis was performed by the cytohubba tool. The four algorithms, maximum neighborhood component (MNC), density of maximum neighborhood component (DMNC), maximal clique centrality (MCC) and degree (Deg), were used as reference standards. The darker the color, the higher the sequence. The sequence of each common gene in the four algorithms were integrated. The abscissa represented 12 key common targets. (b) This was a protein–protein interaction (PPI) network graph, which showed the interrelationships between the 66 common targets. Each circle represented one common target. The color in the graph was adjusted according to the degree value. The deeper the color, the larger the degree value. The genes in the center of the circle were the 12 key genes that had been calculated using topological analysis.