scholarly journals Determining a Reasonable Range of Relative Numerical Tolerance Values for Simulating Deterministic Models of Biochemical Reactions

2018 ◽  
Vol 25 (12) ◽  
pp. 1361-1364 ◽  
Author(s):  
Ming Yang ◽  
Louis Z. Yang
2018 ◽  
Author(s):  
Ming Yang ◽  
Louis Z. Yang

ABSTRACTWhat values of relative numerical tolerance should be chosen in simulation of a deterministic model of a biochemical reaction is unclear, which impairs the modeling effort since the simulation outcomes of a model may depend on the relative numerical tolerance values. In an attempt to provide a guideline to selecting appropriate numerical tolerance values in simulation of in vivo biochemical reactions, reasonable numerical tolerance values were estimated based on the uncertainty principle and assumptions of related cellular parameters. The calculations indicate that relative numerical tolerance values can be reasonably set at or around 10−4 for the concentrations expressed in ng/L. This work also suggests that further reducing relative numerical values may result in erroneous simulation results.


Author(s):  
A.V. Shitikova ◽  
◽  
A.A. Abiala

The results of studies on the role of growth biostimulants in the exogenous regulation of potato productivity on sod-podzolic soils of the Moscow region are presented.Studies have established the specificity of the action of phytohormones.The stimulating effect of the drugs manifested itself in the intensification of metabolic processes, changing the direction of biochemical reactions, which led to an increase in productivity.


1971 ◽  
Vol 2 (3) ◽  
pp. 146-166 ◽  
Author(s):  
DAVID A. WOOLHISER

Physically-based, deterministic models, are considered in this paper. Physically-based, in that the models have a theoretical structure based primarily on the laws of conservation of mass, energy, or momentum; deterministic in the sense that when initial and boundary conditions and inputs are specified, the output is known with certainty. This type of model attempts to describe the structure of a particular hydrologic process and is therefore helpful in predicting what will happen when some change occurs in the system.


2000 ◽  
Vol 42 (3-4) ◽  
pp. 265-272 ◽  
Author(s):  
T. Inoue ◽  
Y. Nakamura ◽  
Y. Adachi

A dynamic model, which predicts non-steady variations in the sediment oxygen demand (SOD) and phosphate release rate, has been designed. This theoretical model consists of three diffusion equations with biochemical reactions for dissolved oxygen (DO), phosphate and ferrous iron. According to this model, step changes in the DO concentration and flow velocity produce drastic changes in the SOD and phosphate release rate within 10 minutes. The vigorous response of the SOD and phosphate release rate is caused by the difference in the time scale of diffusion in the water boundary layer and that of the biochemical reactions in the sediment. Secondly, a negative phosphate transfer from water to sediment can even occur under aerobic conditions. This is caused by the decrease in phosphate concentration in the aerobic layer due to adsorption.


2019 ◽  
Vol 19 (6) ◽  
pp. 413-425 ◽  
Author(s):  
Athanasios Alexiou ◽  
Stylianos Chatzichronis ◽  
Asma Perveen ◽  
Abdul Hafeez ◽  
Ghulam Md. Ashraf

Background:Latest studies reveal the importance of Protein-Protein interactions on physiologic functions and biological structures. Several stochastic and algorithmic methods have been published until now, for the modeling of the complex nature of the biological systems.Objective:Biological Networks computational modeling is still a challenging task. The formulation of the complex cellular interactions is a research field of great interest. In this review paper, several computational methods for the modeling of GRN and PPI are presented analytically.Methods:Several well-known GRN and PPI models are presented and discussed in this review study such as: Graphs representation, Boolean Networks, Generalized Logical Networks, Bayesian Networks, Relevance Networks, Graphical Gaussian models, Weight Matrices, Reverse Engineering Approach, Evolutionary Algorithms, Forward Modeling Approach, Deterministic models, Static models, Hybrid models, Stochastic models, Petri Nets, BioAmbients calculus and Differential Equations.Results:GRN and PPI methods have been already applied in various clinical processes with potential positive results, establishing promising diagnostic tools.Conclusion:In literature many stochastic algorithms are focused in the simulation, analysis and visualization of the various biological networks and their dynamics interactions, which are referred and described in depth in this review paper.


Author(s):  
Anindo Bhattacharjee

The romanticism of management for numbers, metrics and deterministic models driven by mathematics, is not new. It still exists. This is exactly the problem which classical physicists had in the late 19th century until Werner Heisenberg brought the uncertainty principle and opened the doors of quantum physics that challenged the deterministic view of the physical world mostly driven by the Newtonian view. In this paper, we propose an uncertainty principle of management and then list a set of factors which capture this uncertainty quite well and arrive at a new view of scientific management thought. The new view which we call as the Quantum view of Management (QVM) will be based on the major tenets from the ancient philosophical traditions viz., Jainism, Taoism, Advaita Vedanta, Buddhism, Greek philosophers (like Hereclitus) etc.


Author(s):  
Andrew Clarke

Temperature is that property of a body which determines whether it gains or loses energy in a particular environment. In classical thermodynamics temperature is defined by the relationship between energy and entropy. Temperature can be defined only for a body that is in thermodynamic and thermal equilibrium; whilst organisms do not conform to these criteria, the errors in assuming that they do are generally small. The Celsius and Fahrenheit temperature scales are arbitrary because they require two fixed points, one to define the zero and the other to set the scale. The thermodynamic (absolute) scale of temperature has a natural zero (absolute zero) and is defined by the triple point of water. Its unit of temperature is the Kelvin. The Celsius scale is convenient for much ecological and physiological work, but where temperature is included in statistical or deterministic models, only thermodynamic temperature should be used. Past temperatures can only be reconstructed with the use of proxies, the most important of which are based on isotope fractionation.


2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Antonio Sabatini ◽  
Marco Borsari ◽  
Gerard P. Moss ◽  
Stefano Iotti

AbstractAccording to the 1994 IUBMB-IUPAC Joint Commission on Biochemical Nomenclature (JCBN) on chemical and biochemical reactions, two categories of thermodynamics, based on different concepts and different formalisms, are established: (i) chemical thermodynamics, which employ conventional thermodynamic potentials to deal with chemical reactions [1], [2], [3]; and (ii) biochemical thermodynamics, which employ transformed thermodynamic quantities to deal with biochemical reactions based on the formalism proposed by Alberty [4], [5], [6], [7]. We showed that the two worlds of chemical and biochemical thermodynamics, which so far have been treated separately, can be reunified within the same thermodynamic framework. The thermodynamics of chemical reactions, in which all species are explicitly considered with their atoms and charge balanced, are compared with the transformed thermodynamics generally used to treat biochemical reactions where atoms and charges are not balanced. The transformed thermodynamic quantities suggested by Alberty are obtained by a mathematical transformation of the usual thermodynamic quantities. The present analysis demonstrates that the transformed values for ΔrG′0 and ΔrH′0 can be obtained directly, without performing any transformation, by simply writing the chemical reactions with all the pseudoisomers explicitly included and the elements and charges balanced. The appropriate procedures for computing the stoichiometric coefficients for the pseudoisomers are fully explained by means of an example calculation for the biochemical ATP hydrolysis reaction. It is concluded that the analysis reunifies the “two separate worlds” of conventional thermodynamics and transformed thermodynamics.


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