Modelling biological controls

Wilson MJ, Glen DM, Hamacher GM, Smith JU. A model to optimize biological control of slugs using nematode parasites. Appl Soil Ecol. 2004 26 179-191. 

Data preparation and quality control is a key step in applying Free-Wilson methodology to model biological data. Care must be taken to make sure the underlying data complies with F-W additive assumption. 

Desorption from an oil-water multilaminate should be an accurate model for controlled release from liposomes and lipid multilayers and may be helpful to understand transport through naturally occurring biological laminates such as stratum corneum. Asymptotic solutions based upon simple assumptions about the concentration profile may also be used to understand the desorption properties. 

As previously mentioned, the glucose-insulin control system is often regarded as a simple system to keep the plasma glucose concentration within narrow limits. In this context it has been compared to technical control systems and described by simple, often linear or linearized models. Section 6.2 of this chapter gives an outline of classic control and underlines some of the peculiarities of biological control systems. 

A simple way to circumvent the problem and improve the control is to use predictive control, often called feed forward. The idea is to use a control signal, CCff, which in some way reflects the expected time-course of CC that is needed to keep CO close to CL In technical systems this control is frequently called model predictive control (MPC [12]), because CCff is typically derived from a mathematical model. In biological systems, the feed forward is mostly delivered by nerve signals, more rarely by hormones. 

These two complementary systems allow the bacterial cell to metabolize lactose in response to two stimuli. Switching on the expression of the lac operon requires both the absence of glucose and the presence of lactose. This series of switches allows complex expression patterns to be built up from simple components. For this reason, the lac system is a model for other, apparently more complex, biological control systems, such as hormone action or embryonic development. 

Land, S.C., and N.J. Bernier (1995). Estivation metabolic suppression, mechanisms and models of control. In Biochemistry and Molecular Biology of Fishes 5, pp. 381 405, ed. P.W. Hochachka and T.P. Mommsen. Amsterdam Elsevier Science. 

Biological Control of Crop Diseases, edited by Samuel S. Gnanamanickam Pesticides in Agriculture and the Environment, edited by Willis B. Wheeler Mathematical Models of Crop Growth and Yield, Allen R. Overman and Richard V. Scholtz III... 

A second approach to the problem of difficult to obtain measurements is knowledge-based or model-based control. Knowledge-based systems attempt to use various types of knowledge of the biological process (rules etc.) to supplement traditional mathematical control approaches.16 Expert systems are one type of knowledge-based control. Model-based control systems use a model of the process as part of the control algorithm their reliability depends on the accuracy of the model. 

Hukkanen, E.J. A Systems Approach to the Modeling and Control of Molecular, Microparticle, and Biological Distributions. Ph.D. thesis. University of Illinois at Urbana-Champaign Illinois, 2004. 

The ability to retain anisotropic spin interactions and the power to selectively suppress unwanted interactions using pulse sequences such as PISEMA in aligned solids have played a significant role in the applications of solid-state NMR spectroscopy. In addition, the excellent control over the order parameter (ranging from isotropic to rigid solids) of a system and creation of model biological systems obviously invited, simplified, created, and amplified the applications of solid-state NMR techniques. Although solid-state NMR... 

Thibault, J., Taylor, D., and Eonteix, C. (2001). Multicriteria optimization for the production of gluconic acid. 8 International Conference on Computer Applications in Biotechnology Modeling and Control of Biological Processes, Quebec City, Canada, 24-27. 

Smolen P., Baxter D. A. and Byrne J. H. (2000). Modeling transcriptional control in gene network-methods, recent results and future directions. Bulletin of Mathematical Biology. 62, pp 247-292. 

Our initial studies of dynamics in biochemical networks included spatially localized components [32]. As a consequence, there will be delays involved in the transport between the nuclear and cytoplasmic compartments. Depending on the spatial structure, different dynamical behaviors could be faciliated, but the theoretical methods are useful to help understand the qualitative features. In other (unpublished) work, computations were carried out in feedback loops with cyclic attractors in which a delay was introduced in one of the interactions. Although the delay led to an increase of the period, the patterns of oscillation remained the same. However, delays in differential equations that model neural networks and biological control systems can introduce novel dynamics that are not present without a delay (for example, see Refs. 57 and 58). 

Smith, L. (1994) Computer simulation model for biological control of maize weevil by the parasitoids, Anisopteromalus calandrae. Proceedings of the 6th International Working Conference on Stored Product Protection, 2, 1147-1151. 

Our approach to proxy validation and development is based on complementary steps in exploring the inorganic chemistry, inorganic isotope fractionation and biological controls on proxy relationships in organisms relevant to climate reconstructions. In many cases, the integration of laboratory experiments, field and culmre studies, theoretical considerations and numerical modelling has turned out to be a successful method for this task. 

The balance of this paper will be devoted to a model that has been used to facilitate the understanding of a complex biological control system. The erythropoietic system is relatively simple. However, when the interactions of associated physiological systems are considered, the control of erythropoiesis becomes highly interactive and complex. 

The chemical modification of CDs by covalently linked photoactive units was performed to control complexation phenomena by light, for modelling biological photoregulated systems and for developing photochemical mol-... 

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