A practically efficient algorithm for identifying critical control proteins in directed probabilistic biological networks.

ABSTRACT: Network controllability is unifying the traditional control theory with the structural network information rooted in many large-scale biological systems of interest, from intracellular networks in molecular biology to brain neuronal networks. In controllability approaches, the set of minimum driver nodes is not unique, and critical nodes are the most important control elements because they appear in all possible solution sets. On the other hand, a common but largely unexplored feature in network control approaches is the probabilistic failure of edges or the uncertainty in the determination of interactions between molecules. This is particularly true when directed probabilistic interactions are considered. Until now, no efficient algorithm existed to determine critical nodes in probabilist

SUBMITTER: Tokuhara Y 

PROVIDER: S-EPMC11319667 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature