Structural controllability of unidirectional bipartite networks
Open Access
- 10 April 2013
- journal article
- research article
- Published by Springer Science and Business Media LLC in Scientific Reports
- Vol. 3 (1), srep01647-8
- https://doi.org/10.1038/srep01647
Abstract
The interactions between fundamental life molecules, people and social organisations build complex architectures that often result in undesired behaviours. Despite all of the advances made in our understanding of network structures over the past decade, similar progress has not been achieved in the controllability of real-world networks. In particular, an analytical framework to address the controllability of bipartite networks is still absent. Here, we present a dominating set (DS)-based approach to bipartite network controllability that identifies the topologies that are relatively easy to control with the minimum number of driver nodes. Our theoretical calculations, assisted by computer simulations and an evaluation of real-world networks offer a promising framework to control unidirectional bipartite networks. Our analysis should open a new approach to reverting the undesired behaviours in unidirectional bipartite networks at will.This publication has 36 references indexed in Scilit:
- Network medicine: a network-based approach to human diseaseNature Reviews Genetics, 2010
- Link communities reveal multiscale complexity in networksNature, 2010
- Improved network performance via antagonism: From synthetic rescues to multi‐drug combinationsBioEssays, 2010
- Optimal drug combinations and minimal hitting setsBMC Systems Biology, 2009
- A global view of drug-therapy interactionsBMC Pharmacology, 2008
- Drug-therapy networks and the prediction of novel drug targetsJournal of Biology, 2008
- Finding multiple target optimal intervention in disease‐related molecular networkMolecular Systems Biology, 2008
- A model of Internet topology using k -shell decompositionProceedings of the National Academy of Sciences of the United States of America, 2007
- The human disease networkProceedings of the National Academy of Sciences of the United States of America, 2007
- Network biology: understanding the cell's functional organizationNature Reviews Genetics, 2004