Unscented Kalman filter with parameter identifiability analysis for the estimation of multiple parameters in kinetic models

Sun X, Jin L, Xiong M: Extended Kalman filter for estimation of parameters in nonlinear state-space models of biochemical networks. PLoS ONE 2008, 3: e3758. 10.1371/journal.pone.0003758

Lillacci G, Khammash M: Parameter estimation and model selection in computational biology. PLoS Comput Biol 2010, 6: e1000696. 10.1371/journal.pcbi.1000696

Mendes P, Kell D: Non-linear optimization of biochemical pathways: applications to metabolic engineering and parameter estimation. Bioinformatics 1998,14(10):869-883. 10.1093/bioinformatics/14.10.869

Kirkpatrick S, Gelatt CD, Vecchi MP: Optimization by simulated annealing. Science 1983, 220: 671-680. 10.1126/science.220.4598.671

Moles CG, Mendes P, Banga JR: Parameter estimation in biochemical pathways: a comparison of global optimization methods. Genome Res 2003, 13: 2467-2474. 10.1101/gr.1262503

Quach M, Brunel N, d'Alche Buc F: Estimating parameters and hidden variables in non-linear state-space models based on ODEs for biological networks inference. Bioinformatics 2007, 23: 3209-3216. 10.1093/bioinformatics/btm510

Julier S, Uhlmann J: Unscented filtering and nonlinear estimation. Proc IEEE 2004,92(3):401-422. 10.1109/JPROC.2003.823141

Kandepu R, Foss B, Imsland L: Applying the unscented Kalman filter for nonlinear state estimation. J Process Control 2008,18(7-8):753-768. 10.1016/j.jprocont.2007.11.004

Yue H, Brown M, Knowles J, Wang H, Broomhead DS, Kell DB: Insights into the behaviour of systems biology models from dynamic sensitivity and identifiability analysis: a case study of NF-kB signaling pathway. Mol Biosyst 2006, 2: 640-649. 10.1039/b609442b

Yao KZ, Shaw BM, Kou B, McAuley KB, Bacon DW: Modeling ethylene/butene copolymerization with multi-site catalysts: parameter estimability and experimental design. Polym React Eng 2003,11(3):563-588. 10.1081/PRE-120024426

Geffen D: Parameter identifiability of biochemical reaction networks in systems biology. Masters Thesis, Department of Chemical Engineering, Queen's University, Kingston 2008.

Rohwer JM, Botha FC: Analysis of sucrose accumulation in the sugar cane culm on the basis of in vitro kinetic data. Biochem J 2001,358(2):437-445. 10.1042/0264-6021:3580437

Chen WW, Niepel M, Sorger PK: Classic and contemporary approaches to modeling biochemical reactions. Genes Dev 2010,24(17):1861-1875. 10.1101/gad.1945410

Quaiser T, Monnigmann M: Systematic identifiability testing for unambiguous mechanistic modeling--application to JAK-STAT, MAP kinase, and NK-kB signaling pathway models. BMC Syst Biol 2009, 3: 50. 10.1186/1752-0509-3-50

Asprey SP, Macchietto S: Dynamic Model Development: Methods, Theory and Applications. Elsevier, Amsterdam; 2003.

Jacquez JA, Greif P: Numerical parameter identifiability and estimability: integrating identifiability, estimability, and optimal sampling design. Math Biosci 1985,77(1-2):201-227. 10.1016/0025-5564(85)90098-7

Degenring D, Froemel C, Dikta G, Takors R: Sensitivity analysis for the reduction of complex metabolism models. J Process Control 2004,14(7):729-745. 10.1016/j.jprocont.2003.12.008

Terejanu GA: Unscented Kalman filter tutorial.[ http://users.ices.utexas.edu/~terejanu/files/tutorialUKF.pdf ]

Baker RD: A methodology for sensitivity analysis of models fitted to data using statistical methods. IMA J Manag Math 2001,12(1):23-39. 10.1093/imaman/12.1.23

Brennan C: Notes on numerical differentiation. School of Electronic Engineering, Dublin City University.[ http://elm.eeng.dcu.ie/~ee317/Course_Notes/handout1.pdf ]

Kalman Intro, PSAS[ http://psas.pdx.edu/KalmanIntro/ ]

Julier SJ, Uhlmann JK: A new extension of the Kalman filter to nonlinear systems. International Symposium on Aerospace/Defense Sensing, Simulation and Controls 1997., 3: