Network Dynamics as an Inverse Problem

Casadiego Bastidas, Jose Luis

Reconstruction, Design and Optimality

dc.contributor.advisor	Timme, Marc Prof. Dr.
dc.contributor.author	Casadiego Bastidas, Jose Luis
dc.date.accessioned	2016-12-16T09:44:09Z
dc.date.available	2016-12-16T09:44:09Z
dc.date.issued	2016-12-16
dc.identifier.uri	http://hdl.handle.net/11858/00-1735-0000-002B-7CE4-3
dc.identifier.uri	http://dx.doi.org/10.53846/goediss-6042
dc.language.iso	eng	de
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.ddc	571.4	de
dc.title	Network Dynamics as an Inverse Problem	de
dc.title.alternative	Reconstruction, Design and Optimality	de
dc.type	doctoralThesis	de
dc.contributor.referee	Kree, Reiner Prof. Dr.
dc.date.examination	2016-01-13
dc.description.abstracteng	In this thesis, we take a general view on the study of networks from inverse perspectives. By proposing a general representation for the dynamics of networks in terms of explicit dependencies among units, we develop new concepts for understanding, among other things, (i) how disparate networks achieve identical dynamics, and (ii) how we may reconstruct the structural connectivity of networks regardless of the type of network under study (e.g. gene regulatory networks, metabolic networks or neural networks). Specifically, here we heavily rely on concepts and tools coming from nonlinear dynamics and linear algebra to introduce physics-inspired inverse approaches for explaining the fundamental mechanisms for revealing connections in networks. Furthermore, the content and results of this thesis are self-sufficient, such that the reader may not need to refer to additional scientific sources.	de
dc.contributor.coReferee	Parlitz, Ulrich Prof. Dr.
dc.contributor.thirdReferee	Herminghaus, Stephan Prof. Dr.
dc.contributor.thirdReferee	Geisel, Theo Prof. Dr.
dc.contributor.thirdReferee	Cramer, Patrick Prof. Dr.
dc.subject.eng	network + inference + reconstruction + inverse + dynamics + inferring + revealing + reconstructing + dynamical + systems + correlations + transfer + entropy + synaptic + connectivity + neural + connections + links + reveal + discover + ARNI + event + space	de
dc.subject.eng	explict + dependencies	de
dc.identifier.urn	urn:nbn:de:gbv:7-11858/00-1735-0000-002B-7CE4-3-7
dc.affiliation.institute	Göttinger Graduiertenschule für Neurowissenschaften, Biophysik und molekulare Biowissenschaften (GGNB)	de
dc.subject.gokfull	Biologie (PPN619462639)	de
dc.identifier.ppn	875067662

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Beschreibung:: Doctoral thesis

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Das Dokument erscheint in:

GGNB - Göttinger Graduiertenzentrum für Neurowissenschaften, Biophysik und molekulare Biowissenschaften [1115]
GGNB - Göttingen Graduate Center for Neurosciences, Biophysics and Molecular Biosciences

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