Biomathematical model

The radioligand not only has to satisfy this large array of demanding criteria, but also has to present pharmacokinetics that can be modelled biomathematically to deliver accurate binding parameters (e.g., binding potential). A particular administration protocol may be needed to achieve this aim, based on one, two or three separate injections of radioligand, usually at varied specific radioactivity. If the biomathematical model requires an arterial input function, information on the appearance of radioactive metabolites in plasma may be required in each PET experiment. 

Nevertheless, there is no need to resign. According to biomathematical modeling, only 3% of all antibacterial agents synthesized in Streptomyces have been reported so far [37]. Additionally, less than 10% of the world s biodiversity has been tested for biological activity, and many more useful natural lead compounds are yet to be discovered [47]. 

Biomathematics is being used to model the workings of a heart in order to improve artificial heart valves. With biomathematics models, designs can be tested more quickly and efficiendy. 

Medical Uses. Biomathematical models have been developed to illustrate various functions within the... 

Walter, E., Identifiability of State Space Models. Lecture notes in "Biomathematics, Vol. 46. Springer-Verlag, Berlin and New York, 1982. 

That is, the known methods do not work, as shown explicitly in N. Dubin, A Stochastic Model for Immunological Feedback in Carcinogenesis (Lecture Notes in Biomathematics Nr. 9 Springer, Berlin 1976). 

Biomathematics and statistics relate to many areas of toxicology. They deal with data analysis, the determination of significance, and the formulation of risk estimates and predictive models. 

Newton, C. M. (1980) Biomathematics in oncology modelling of cellular systems. Ann. Rev. Biophys. Bioeng. 9, 541. 

For a matrix model to be valid, enough matrix multiplications must be done for the stable age distribution to be reached. This occurs when the growth rate (X) stabilizes. Some modeling programs, such as RAMAS GIS (Applied Biomathematics, Setauket, New York), precalculate the stable age distribution and the starting vector is in the stable age distribution. 

DeAngelis DL, Rose KA, Huston MA. 1994. Individual-oriented approaches to modeling ecological populations and communities. In Levin SA, editor. Frontiers in mathematical biology. Lecture notes in biomathematics. Vol. 100. Berlin Springer, p 390-410. 

J. L. Hudson and O. E. Rossler, Chaos in simple three- and four-variable systems, in Modeling of patterns in space and time (Lecture notes in biomathematics, vol. 55), W. Jager and J. D. Murray, eds., Springer, Berlin, 1984 see also Gray and Scott (ref. G2), Section 13.4. 

Hofmann W, Graham RC, Martonen TB. Human subject age and activity level factors addressed in a biomathematical deposition program for extrapolation modeling. Health Phys 1989 57(suppl l) 49-59. 

Takeuchi, Y. Adachi, N. (1983b). Oscillations in prey-predator models. In Population biology, eds H. I. Friedman H. F. Strobek, Lecture Notes in Biomathematics, vol. 52, pp. 320-6. Springer Verlag, Berlin. 

Walter, Ch. (1977). Contribution to the enzyme models. In Mathematical models of biological discovery. Lecture Notes in Biomathematics, Vol. 13, pp. 39-94. Springer Verlag, Berlin. 

In addition to the direct utility of mathematical models in the analysis of complex chemical systems a unified conceptual framework is offered to the mathematical treatment of problems of chemical kinetics and related areas in biomathematics. Biochemical control processes, oscillation and fluctuation phenomena in neurochemical systems, coexistence and extinction in populations, prebiological evolution and certain ecological problems of Lake j Balaton can be treated in terms of this framework. Though the main body of/ the book deals with spatially homogeneous systems, spatial structures in chemical systems, pattern formation and morphogenesis related to reaction-diffusion models are also mentioned briefly. 

The use of biomathematics is not limited to modeling a biological function and includes other techniques, such as structuring and analyzing data. Scientists may use biomathematics to oi nize data or analyze data sets, and statistics are often considered an integral tool. 

Scientists are using biomathematics to create a virtual patient. First, biomathematics is used to model the human body. Using the virtual patient, scientists can test cancer-prevention drugs. The result is a quicker and cheaper way to develop drugs. 

Biomathematics has applications in nature. By using biomathematics, the pigment patterns of a leopard s spots or the patterns of seasheUs can be modeled. 

Mathematical models of biofibns systems, which are layers of usually nonresistant microorganisms such as bacteria that attach to a surface, are critical to the medical and technical industries. Biofibn systems can cause infections in humans and corrosion and deterioration in technical systems. Biomathematics can be used to model biofilms systems to help understand and prevent their formation. 

Important future applications for biomathematics will be in the bioengineering and medical industries. The development of mathematical models for complex biological phenomena will aid scientists in a deeper understanding that can lead to more effective treatments in such areas such as tumor therapy. As new tools and methods continue to develop, biomathematics will be a field that expands to sort and analyze the large influx of data. 

While mathematical tools have been applied to biology for some time, many scientists believe there is still a need for increased quantitative analysis of biology. Some call for more emphasis on mathematics in high school and undergraduate biology classes. They believe that this will advance biomathematics. As more universities develop biomathematics departments and degrees, more mathematics classes will be added to the curriculum. A concern has been raised in the biomathematics field about the assumptions used to create simplified mathematical models. More complex and accurate models will likely be developed. 

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