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Structural characteristics in network control of molecular multiplex networks.
Yuan, Cheng; Qian, Zu-Yu; Zhou, Jie; Chen, Shi-Ming; Nie, Sen.
Afiliação
  • Yuan C; School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, Jiangxi, People's Republic of China.
  • Qian ZY; School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, Jiangxi, People's Republic of China.
  • Zhou J; School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, Jiangxi, People's Republic of China.
  • Chen SM; School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, Jiangxi, People's Republic of China.
  • Nie S; School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, Jiangxi, People's Republic of China.
PLoS One ; 18(3): e0283768, 2023.
Article em En | MEDLINE | ID: mdl-36996151
ABSTRACT
Numerous real-world systems can be naturally modeled as multilayer networks, providing an efficient tool to characterize these complex systems. Although recent progress in understanding the controlling of synthetic multiplex networks, how to control real multilayer systems remains poorly understood. Here, we explore the controllability and energy requirement of molecular multiplex networks coupled by transcriptional regulatory network (TRN) and protein-protein interaction (PPI) network from the perspective of network structural characteristics. Our findings reveal that the driver nodes tend to avoid essential or pathogen-related genes. However, imposing external inputs on these essential or pathogen-related genes can remarkably reduce the energy cost, implying their crucial role in network control. Moreover, we find that the minimal driver nodes, as well as the energy required, are associated with disassortative coupling between TRN and PPI networks. Our results provide a comprehensive understanding of the roles of genes in biology and network control across several species.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Mapas de Interação de Proteínas Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Mapas de Interação de Proteínas Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article