Year: 2018
Type: article
Abstract: SUMMARY: Biological processes are often modeled by ordinary differential equations with unknown parameters. The unknown parameters are usually estimated from experimental data. In some cases, due to the structure of the model, this estimation problem does not have a unique solution even in the case of continuous noise-free data. It is therefore desirable to check the uniqueness a priori before carrying out actual experiments. We present a new software SIAN (Structural Identifiability ANalyser) that does this. Our software can tackle problems that could not be tackled by previously developed packages. AVAILABILITY AND IMPLEMENTATION: SIAN is open-source software written in Maple and is available at https://github.com/pogudingleb/SIAN. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Source: Bioinformatics
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Awards: G1371083205, FRG: Collaborative Research: Model Theory of Differential and Difference Equations with Applications, G2324219109, G2505674234, G3914215863, G4282460723, G4531453472, AF: Medium: Collaborative Research: Numerical Algebraic Differential Equations, AF: Medium: Collaborative Research:Numerical Algebraic Differential Equations, AF: Small: Quantifier elimination by group analysis, International Symposium on Symbolic and Algebraic Computation, G6121083166, G6378149398, G7845798442
OpenAlex ID: W2949814822