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Controllability of complex networks

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dc.contributor.author Chohan, Dicksha
dc.contributor.author Bagler, Ganesh (Advisor)
dc.date.accessioned 2018-07-21T06:08:04Z
dc.date.available 2018-07-21T06:08:04Z
dc.date.issued 2017-05
dc.identifier.uri http://repository.iiitd.edu.in/xmlui/handle/123456789/620
dc.description.abstract Self-organized systems are known to be characterized with inherent complexity and hence are difficult to control. This complexity arises out of subtle interconnections among its subunits. Graph theory has emerged as a relevant paradigm for modeling and characterization of such complex systems, as well as for finding means of their control. Using the concept of controllability from control systems, one can identify ‘driver nodes’ that could be used to gain control of the system through external inputs. In this thesis, we used controllability analysis for investigating the control mechanisms of three networks: Airport Network of India, C. elegans Neuronal Network, and Yeast Gene Regulatory Network. All of these systems contain an underlying directional network that is essential for their efficient functioning. For Airport Network of India, we constructed weighted directed graphs, representing transportation channels across India in 2004 and 2016. Apart from studying evolution of network topology for this air transportation network, we also examined its efficiency. We find that controllability analysis can identify set of nodes critical for its efficiency as well as those acting as its bottlenecks. Further, we studied the neuronal network of C. elegans to identify set of minimal edges (synapses) that can switch its mode of control (from centralized to distributed and vice versa). Finally, we investigated the gene regulatory network of yeast to identify its driver and non-driver genes, and to probe their association with biological essentiality, pathways and dug targets. Our studies of these networked systems provide interesting insight into their efficiency, mode of control and biological correlates of driver nodes. We believe that apart from adding to our understanding of these complex systems, our work provides insightful directions for their control en_US
dc.language.iso en_US en_US
dc.subject Complex networks en_US
dc.subject Network controllability en_US
dc.title Controllability of complex networks en_US
dc.type Thesis en_US

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