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Conserved Control Path in Multilayer Networks.
Wang, Bingbo; Ma, Xiujuan; Wang, Cunchi; Zhang, Mingjie; Gong, Qianhua; Gao, Lin.
Afiliação
  • Wang B; School of Computer Science and Technology, Xidian University, Xi'an 710071, China.
  • Ma X; School of Computer Science and Technology, Xidian University, Xi'an 710071, China.
  • Wang C; School of Computer Science and Technology, Xidian University, Xi'an 710071, China.
  • Zhang M; School of Computer Science and Technology, Xidian University, Xi'an 710071, China.
  • Gong Q; School of Computer Science and Technology, Xidian University, Xi'an 710071, China.
  • Gao L; School of Computer Science and Technology, Xidian University, Xi'an 710071, China.
Entropy (Basel) ; 24(7)2022 Jul 15.
Article em En | MEDLINE | ID: mdl-35885201
The determination of directed control paths in complex networks is important because control paths indicate the structure of the propagation of control signals through edges. A challenging problem is to identify them in complex networked systems characterized by different types of interactions that form multilayer networks. In this study, we describe a graph pattern called the conserved control path, which allows us to model a common control structure among different types of relations. We present a practical conserved control path detection method (CoPath), which is based on a maximum-weighted matching, to determine the paths that play the most consistent roles in controlling signal transmission in multilayer networks. As a pragmatic application, we demonstrate that the control paths detected in a multilayered pan-cancer network are statistically more consistent. Additionally, they lead to the effective identification of drug targets, thereby demonstrating their power in predicting key pathways that influence multiple cancers.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article