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Modeling, inference and optimization of regulatory networks based on time series data

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dc.creator Weber, Gerhard-Wilhelm
dc.creator Defterli, Ozlem
dc.creator Kropat, Erik
dc.creator Gok, Sirma Zeynep Alparslan
dc.date 2011-05-15T21:00:00Z
dc.date.accessioned 2020-10-06T11:21:37Z
dc.date.available 2020-10-06T11:21:37Z
dc.identifier bb272bbb-2677-4f99-beca-7c91ec2dff0c
dc.identifier 10.1016/j.ejor.2010.06.038
dc.identifier https://avesis.sdu.edu.tr/publication/details/bb272bbb-2677-4f99-beca-7c91ec2dff0c/oai
dc.identifier.uri http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/70572
dc.description In this survey paper, we present advances achieved during the last years in the development and use of OR, in particular, optimization methods in the new gene-environment and eco-finance networks, based on usually finite data series, with an emphasis on uncertainty in them and in the interactions of the model items. Indeed, our networks represent models in the form of time-continuous and time-discrete dynamics, whose unknown parameters we estimate under constraints on complexity and regularization by various kinds of optimization techniques, ranging from linear, mixed-integer, spline, semi-infinite and robust optimization to conic, e.g., semi-definite programming. We present different kinds of uncertainties and a new time-discretization technique, address aspects of data preprocessing and of stability, related aspects from game theory and financial mathematics, we work out structural frontiers and discuss chances for future research and OR application in our real world. (C) 2010 Elsevier B.V. All rights reserved.
dc.language eng
dc.rights info:eu-repo/semantics/closedAccess
dc.title Modeling, inference and optimization of regulatory networks based on time series data
dc.type info:eu-repo/semantics/article


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