Computer modeling of complex biological systems
:Computer modeling of biological systems, a process of building new sets of conceptualizations, theories, and implementations is cov-ered in depth. The emphasis is on how computer modeling encom-passes three distinct areas of science (computer science, biology, and medicine) for building a framework for investigating the behavior of a complex biological system. Simulation and modeling are dis-cussed because these two factors provide the methodology for the design, development, experimentation, analysis, and evaluation of a experiment under study. Because of their high degree of modular-ity and collective complexity, computer systems such as analog, digital, or hybrid are reviewed. This presentation of computer mod-eling of biological systems delves into the study of data represen-tation (or data structures) and their transformation into an empirical model via a software program.
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Sahin S Sitharama Iyengar and Ramu M
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algorithms analysis arterial pressure behavior biological activity blood pressure blood volume calculated cardiac output cell renewal process cell systems Chem chemical coefficients compartment complex biological system compounds computer model constant cooling period correlation criterion curve data structure design of experiments developed distribution drug design erythropoiesis essential hypertension Estimation of Parameters expected likelihood Figure function given Guyton Guyton-Coleman model heart rate hemodynamic initial input kinetics linear loop mathematical model matrix Mean arterial pressure mean life span mean values method mmHg model discrimination molecular molecule multiresponse models nonlinear model normal obtained oo oo parameter estimation posterior probabilities predicted prior probabilities problem procedure reaction regression relationship renal response retortable pouches rival models RTVAL simulated food statistical steady strand substructure Table temperature thermal processing thiamin tissue Topological tumor tumor cells variance-covariance matrix vector vitamin