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ODEion- a software module for structural identification of ordinary differential equations

Peter Gennemark (Institutionen för matematiska vetenskaper) ; Dag Wedelin (Institutionen för data- och informationsteknik, Datavetenskap (Chalmers))
Journal of Bioinformatics and Computational Biology (0219-7200). Vol. 12 (2014), 1, p. Art. no. 1350015.
[Artikel, refereegranskad vetenskaplig]

In the systems biology field, algorithms for structural identification of ordinary differential equations (ODEs) have mainly focused on fixed model spaces like S-systems and/or on methods that require sufficiently good data so that derivatives can be accurately estimated. There is therefore a lack of methods and software that can handle more general models and realistic data. We present ODEion, a software module for structural identification of ODEs. Main characteristic features of the software are: • The model space is defined by arbitrary user-defined functions that can be nonlinear in both variables and parameters, such as for example chemical rate reactions. • ODEion implements computationally efficient algorithms that have been shown to efficiently handle sparse and noisy data. It can run a range of realistic problems that previously required a supercomputer. • ODEion is easy to use and provides SBML output. We describe the mathematical problem, the ODEion system itself, and provide several examples of how the system can be used. Read More: http://www.worldscientific.com/doi/abs/10.1142/S0219720013500157



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Denna post skapades 2014-01-22. Senast ändrad 2016-07-22.
CPL Pubid: 192981

 

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