Publication date: Mar 25, 2025

The algorithm first identifies the head and tail nodes of the control paths of all control schemes and subsequently identifies the control hubs. The method using total network controllability analysis could also be extended to identify the control hubs of other diseases, for example, the SARS-CoV-2 infectious disease. A novel polynomial-time algorithm was developed to identify all control hubs without the need to compute all control schemes of a network. A network is considered totally controllable if it is possible to manipulate the states of all nodes using a finite set of control inputs applied to specific nodes. The regulatory network constructed in the study is a pan-cancer gene regulatory network suitable for applying network controllability. This analysis helps identify the nodes in a network that are crucial for controlling the system’s behaviour, making them suitable candidates for therapeutic targets. The research team applied the CKG approach and constructed a GRN for bladder cancer (BLCA), which consists of 7,030 nodes (genes) and 103,360 directed edges.

Semantics