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A new computational tool for establishing model parameter identifiability.

Abstract:

We describe a novel method to establish a priori whether the parameters of a nonlinear dynamical system are identifiable--that is, whether they can be deduced from output data (experimental observations). This is an important question as usually identifiability is assumed, and parameters are sought without first establishing whether these can be inferred from a set of measurements. We highlight the connections between parameter identifiability and state observability. We show how observabilit...

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Publication status:
Published

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Publisher copy:
10.1089/cmb.2008.0211

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Institution:
University of Oxford
Department:
Oxford, MPLS, Engineering Science
Journal:
Journal of computational biology : a journal of computational molecular cell biology
Volume:
16
Issue:
6
Pages:
875-885
Publication date:
2009-06-05
DOI:
EISSN:
1557-8666
ISSN:
1066-5277
URN:
uuid:bdf48367-2e0b-4f38-8cdb-eb91d0414097
Source identifiers:
64422
Local pid:
pubs:64422
Language:
English
Keywords:

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