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Parameter Estimation of ODE's with Regression Splines: Application to Biological Networks
Published on Apr 04, 20078650 Views
The construction and the estimation of quantitative models of gene regulatory networks and metabolic networks is one of the task of Systems Biology. Such models are useful because they provide tools f
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Chapter list
Parameter estimation of ODE’s with regression splines: applications to biological networks00:03
Biological networks and dynamical processes00:48
Biological networks and dynamical processes01:08
Assumptions on biochemical kinetics01:36
Outline02:22
Plan02:48
Statistical setting02:50
Statistical setting03:40
Direct estimation04:07
New characterization of the solution05:00
New characterization of the solution05:53
New characterization of the solution05:55
General Principle of two-step estimator06:35
General Principle of two-step estimator07:07
General Principle of two-step estimator07:34
General Principle of two-step estimator07:45
Comments08:20
Comments08:38
Comments08:54
Comments09:10
Computational Advantages09:46
Computational Advantages09:58
Computational Advantages10:30
Plan10:57
Splines11:08
Nonparametric regression12:05
Asymptotics12:24
Asymptotics13:33
Properties14:15
Plan14:50
Repressilator14:53
Evolution of protein concentrations15:37
Nonparametric estimation of the solution by splines15:45
Estimates of the derivative of φn16:14
Estimated parameters16:40
The reconstructed curves17:05
Plan17:28
Conclusion17:32
Conclusion17:59