TY - CHAP
T1 - Systems Analysis for Systems Biology
AU - Hildebrandt, Scott
AU - Bagheri, Neda
AU - Gunawan, Rudiyanto
AU - Mirsky, Henry
AU - Shoemaker, Jason
AU - Taylor, Stephanie
AU - Petzold, Linda
AU - Doyle, Francis J.
N1 - Funding Information:
The authors would like to acknowledge the following sources of funding for the work presented in this chapter. Unfolded protein response: National Institutes of Health under grants R01 GM65507 and R01 GM75297; apoptotic signaling pathway: the National Science Foundation’s IGERT Program under grant DGE02-21715 and the Institute for Collaborative Biotechnologies; Arabidopsis thaliana circadian rhythm: the National Science Foundation’s IGERT Program under grant DGE02-21715, the Institute for Collaborative Biotechnologies through US Army Research Office Grant DAAD19-03-D-0004, and NSF/NIGMS grant GM078993; fruit fly (Drosophila melanogaster) circadian rhythm: the National Science Foundation’s IGERT Program under grant DGE02-21715, the Institute for Collaborative Biotechnologies through US Army Research Office Grant DAAD19-03-D-0004, DARPA BioSPICE Program, and the Research Participation Program between the US DOE and AFRL/HEP; mouse circadian rhythm: the Institute for Collaborative Biotechnologies through US Army Research Office Grant DAAD19-03-D-0004.
PY - 2010
Y1 - 2010
N2 - This chapter focuses on system's analysis tools and its application to the study of biological systems through mathematical modeling. The tools from classical sensitivity analysis are outlined, and described with application to the unraveling of design principles in complex biophysical networks, particularly with regard to robustness. Applications to optimized experimental design, and hypothesis discrimination are also discussed. In the field of systems biology, sensitivity analysis has been used in a number of applications, including optimized design of synthetic circuits, design of experiments for optimal parameter estimation, and robustness analysis to provide insights into design principles. Examples of how these sensitivity analysis implications and extensions have already been applied to biological systems are provided in this chapter. Sensitivity analysis investigates the changes in a system's behavior in response to infinitesimal parametric perturbations. Results from UPR sensitivity comparisons showed the greatest disparity between the BiP-heterologous unfolded protein binding rate sensitivities for the two models. Sensitivity analysis is also used to explore a stochastic, oscillatory system: the mouse circadian rhythm. The fundamental sensitivity analysis concept, or definition, is quite basic: perturbations in model parameters will affect model outputs. However, its implications, extensions, and applications are profound and numerous in the field of systems biology.
AB - This chapter focuses on system's analysis tools and its application to the study of biological systems through mathematical modeling. The tools from classical sensitivity analysis are outlined, and described with application to the unraveling of design principles in complex biophysical networks, particularly with regard to robustness. Applications to optimized experimental design, and hypothesis discrimination are also discussed. In the field of systems biology, sensitivity analysis has been used in a number of applications, including optimized design of synthetic circuits, design of experiments for optimal parameter estimation, and robustness analysis to provide insights into design principles. Examples of how these sensitivity analysis implications and extensions have already been applied to biological systems are provided in this chapter. Sensitivity analysis investigates the changes in a system's behavior in response to infinitesimal parametric perturbations. Results from UPR sensitivity comparisons showed the greatest disparity between the BiP-heterologous unfolded protein binding rate sensitivities for the two models. Sensitivity analysis is also used to explore a stochastic, oscillatory system: the mouse circadian rhythm. The fundamental sensitivity analysis concept, or definition, is quite basic: perturbations in model parameters will affect model outputs. However, its implications, extensions, and applications are profound and numerous in the field of systems biology.
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U2 - 10.1016/B978-0-12-372550-9.00010-9
DO - 10.1016/B978-0-12-372550-9.00010-9
M3 - Chapter
AN - SCOPUS:84882873489
SN - 9780123725509
SP - 249
EP - 272
BT - Systems Biomedicine
PB - Elsevier Inc
ER -