Presentation Information
[SS20-03]Exploring Network Controllability in Complex Biological Networks
*Jose Nacher1 (1. Toho University (Japan))
Keywords:
Network Controllability,Biological Networks,Computational Biology,Systems Biology
Network controllability emerged by combining complex network science and control theory to guide networks toward desired states, demonstrating significant potential in various data-driven applications.The approach aims to identify a small number of nodes that can control the entire system. Various frameworks and methods have been developed to address controllability challenges in large-scale networks. In this talk, I will introduce models and algorithms from our research, as well as related studies, where we have developed control approaches for different types of biological networks, including undirected, directed, bipartite, and multilayer networks.
Data analyses reveal that, beyond identifying driver nodes capable of steering the system, these nodes often correlate with important biological functions. We developed algorithms to efficiently identify such nodes and demonstrated their relevance in biological contexts. These findings open new possibilities for applying network control theory to advance our understanding of large-scale complex biological systems.
Data analyses reveal that, beyond identifying driver nodes capable of steering the system, these nodes often correlate with important biological functions. We developed algorithms to efficiently identify such nodes and demonstrated their relevance in biological contexts. These findings open new possibilities for applying network control theory to advance our understanding of large-scale complex biological systems.