Biological process models

Beck, M.B. "Identification and parameter estimation of biological process models" In "System Simulation in Water Resources", Vansteenkiste, G.C., Ed. North Holland, 1975, 19-44. 

As described by Nielsen et al. (2003), biological process modeling uses a set of mathematical relationships developed through physical laws and/or empirical observations that relate the input variables of the system to the output variables. The input parameters include things such as flow rate(s), pH, temperature, agitation speed, and substrate concentration, while the output may include cell/product concentration, temperature, and flow rate. Kinetic expressions, which describe the... 

The discovery of ribozymes (Section 28.11) in the late 1970s and early 1980s by Sidney Altman of Yale University and Thomas Cech of the University of Colorado placed the RNA World idea on a more solid footing. Altman and Cech independently discovered that RNA can catalyze the formation and cleavage of phosphodiester bonds—exactly the kinds of bonds that unite individual ribonucleotides in RNA. That, plus the recent discovery that ribosomal RNA catalyzes the addition of amino acids to the growing peptide chain in protein biosynthesis, takes care of the most serious deficiencies in the RNA World model by providing precedents for the catalysis of biological processes by RNA. 

The rate model for a biological process is given by a Monod rate model... 

Box models and box-diffusion models have few degrees of freedom and they must describe physical, chemical, and biological processes very crudely. They are based on empirical relations rather than on first principles. Nevertheless, the simple models have been useful for obtaining some general features of the carbon cycle and retain some important roles in carbon cycle research (Craig and Holmen, 1995 Craig et al, 1997 Siegenthaler and joos, 1992). 

The structure and mathematical expressions used in PBPK models significantly simplify the true complexities of biological systems. If the uptake and disposition of the chemical substance(s) is adequately described, however, this simplification is desirable because data are often unavailable for many biological processes. A simplified scheme reduces the magnitude of cumulative uncertainty. The adequacy of the model is, therefore, of great importance, and model validation is essential to the use of PBPK models in risk assessment. 

The diffusion of solutes in water is an important event in many biological processes. The influences of water temperature and hydropathic states of the solute are expected to be of importance in this process. A study modeling diffusion using CA was reported by Kier et al. [6]. The study revealed increases in diffusion rates with higher temperatures and higher solute hydrophobicity. More recent studies indicate that the diffusion rate may be maximum at an intermediate level of hydrophobicity and temperature [7]. 

A final example of the simulation of a complex system is a series of MD simulations of bilayer membranes. Membranes are crucial constituents of living organisms they are the scene for many important biological processes. Experimental data are known for model systems for example for the system sodium decanoate, decanol and water that forms smectic liquid crystalline structures at room temperature, with the lipids organized in bilayers. 

To implement the Physiome Project, a lot of good science (Wolpert) and thinking (Dover) will be required. The tools that will ultimately define the success of the project are analytical models of biological processes that have predictive power - virtual cells, tissues, organs and systems. 

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