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pubmed-article:19176548pubmed:abstractTextIn recent years, the biological literature has seen a significant increase of reported methods for identifying both structure and parameters of ordinary differential equations (ODEs) from time series data. A natural way to evaluate the performance of such methods is to try them on a sufficient number of realistic test cases. However, weak practices in specifying identification problems and lack of commonly accepted benchmark problems makes it difficult to evaluate and compare different methods.lld:pubmed
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pubmed-article:19176548pubmed:articleTitleBenchmarks for identification of ordinary differential equations from time series data.lld:pubmed
pubmed-article:19176548pubmed:affiliationDepartment of Mathematical Sciences, University of Göteborg, SE-412 96 Göteborg, Sweden. peterg@chalmers.selld:pubmed
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