4.1. Modelling in Biology

The method of modeling in biology is a means to establish vsebolee deep and complex relationship between the biological theory and experiment. In the past century, the experimental method in biology began to encounter naopredelennye border, and it turned out that the research can not be a happy bezmodelirovaniya . If you look at some examples of restrictions primeneniyaeksperimenta in biology, then it will be mainly the following : - Experiments can be carried out only on the currently existing objects (the inability to spread in the experiment of the past ) ; - Intervention in biological systems are sometimes of such a nature chtonevozmozhno establish the cause is a change (due to interference or girlfriend reasons) ; - Some theoretically possible experiments are not feasible vsledstvienizkogo level of development of experimental techniques ; - A large group of experiments involving experimentation on human beings should be rejected on moral and ethical grounds . But simulation is widely used in biology, not only because of zatogo that can replace the experiment . It has a great self- importance , which is reflected in the opinion of some authors , a number of advantages: - Using the method of modeling a complex data can be razrabotattsely number of different models , different interpretation of the phenomenon under investigation , ivybrat most fruitful ones for the theoretical interpretation ; - In the process of building a model can make different supplement to get her issleduemoygipoteze and simplification; - In the case of complex mathematical models can be used a computer; - Opens the possibility of modeling experiments ( sintezaminokislot , experiments in laboratory animals ) . All this clearly shows that the simulation performs samostoyatelnyefunktsii in biology and is increasingly necessary step in the process of developing a theory . Odnakomodelirovanie retains its heuristic value only when uchityvayutsyagranitsy use any model. Especially impressively shown by RS Karpinskoyna minimal cell model . This model emerged as a result of cognition биохимическойуниверсальности life and has methodological significance for the simulation of the main eezakonomernostey . Minimal cell model representing the basic unit of life covers only the membrane , re- output system and the system of energy supply . Thus, the objective is to reproduce with it most obschiezhiznennye structure. And although it remains unreported aspect of development , the model of minimum kletkiimeet essential to prove the unity of the organic world. However etamodel not beyond the biochemical approach to life, which is predominantly "aims to prove its stable , universal and immutable characteristics." On the other hand, the minimum cell model may be used , and certain qualitative dlyarazgranicheniya stages of development. She and lyubayadrugaya model has a range of applicability and can recognize certain patterns irekonstruirovat . Thus, this model vypolnyaetsuschestvennye functions during development of the theory . For a deeper understanding of the meaning and essence of modeling biologiisleduet dwell on the problems of modeling in the history of biological science. Modeling, as the scientific method in biology was first described by Otto and soznatelnoispolzovano Byuchii and Stephen Leduc in 1892. From the point of view of history naukiinteresno that simulation methods in biology have been used deliberately lishtogda when, thanks to the appearance of Darwin's theory of evolution and the creation of genetics in a development of biological theory was made a major leap , and biology overstepped kissledovaniyu increasingly complex biotic relationships . For example , the emergence of population genetics is closely linked with the model of Hardy Weinberg . Deep penetration in relation to the objective of macro-and mikrourovnyahzhivogo , as well as the transition to the study of super-organism systems issledovateleyobratitsya forced to modeling method . All changes in estestvennyhpopulyatsiyah , are very complex because of the nature of the interaction of many faktorovevolyutsii , so that only the study of simpler models can provide insight into some of the aforesaid evolutionary factors . Modeling has played a significant role in the development and plays molekulyarnoybiologii . One of the known examples of the application of modeling techniques yavlyaetsyarazrabotka structural model of DNA , which are based on рентгеноструктурногоанализа and chemical research , and interpreted the Watson and Crick ( 1953 ) . Etamodel particularly impressively shows the relationship between экспериментальнымиметодами kmetodami modeling for the further development of biological theory . Issues related to the further use of molecular modeling in biologiishiroko considered in the German researcher A. Thomas . 4.2 . About cybernetic modeling and human modelirovaniimyslitelnoy

In the modern scientific knowledge is quite widespread tendency postroeniyakiberneticheskih object models a variety of classes. " Cybernetic stage vissledovanii : complex systems marked by a significant transformation of the" language of science " , is characterized by the possibility of expression of the main features of these systems in terminahteorii information and management . This has made available their mathematical analysis . " Cybernetic modeling is used and as a general heuristic tool , and kakiskusstvenny body , and how the system substitute , and the function of the demonstration . The use of cybernetic theory of communication and control for constructing models for consistency areas based on the maximal generality of its laws iprintsipov for objects of nature , social systems and technical systems. The widespread use of cybernetic modeling allows rassmatrivatetot " logical and methodological " phenomenon as an integral element of " intellektualnogoklimata " modern science . " In this context, talk about a special " cyber stilemyshleniya "the" cybernetization "scientific knowledge. With cybernetic modelirovaniemsvyazyvayutsya possible directions of growth processes of theorization of the various sciences , increasing the level of theoretical research. Consider some examples describing the inclusion of cybernetic ideas to other conceptual sistemy.Analiz biological systems using cybernetic modeling obychnosvyazyvayut with the need to explain some of the mechanisms of their functioning ( will see this below , considering the modeling of human mental activity ) . Vetom case, the system of cybernetic concepts and principles is a source gipotezotnositelno any self-managing systems , because the idea of ​​communication and control are valid for use etoyoblasti ideas , new classes of factors. Describing the process of cybernetic modeling , pay attention to inherit the circumstances . Model, being analogous to the phenomenon under investigation , never feels bad to reach the degree of complexity of the latter. When building models use kizvestnym simplifications purpose - the desire not to display the entire object , and smaksimalnoy completeness describe some of his " cut ." The problem is that by introducing a number of simplifying assumptions to highlight important issledovaniyasvoystva . By creating a cybernetic model release information upravlencheskiesvoystva . All other aspects of this subject are left out . On chrezvychaynuyuvazhnost search for ways to study complex systems by applying assumptions opredelennyhuproschayuschih indicates Ashby . "In the past , he notes, nablyudalosnekotoroe disregard for the simplification ... However, we are dealing with issledovaniemslozhnyh systems that can not afford such neglect . Slozhnyhsistem researchers must deal with simplified forms , for comprehensive issledovaniyabyvayut often quite impossible." Analyzing the process of application of cybernetic simulation razlichnyhoblastyah knowledge , you can see the expansion of the scope of application of cybernetic models: the use of brain science , sociology , art, and in a number of technical sciences. Vchastnosti in modern measurement techniques have found application informatsionnyemodeli . Arose on the basis of information theory of measurement and izmeritelnyhustroystv - a new sub-section of modern applied metrology. In the tasks in a variety of classes using the principle of feedback. In the proposed model of motivation chastnostiDeych behavior based on this principle. This modelpozvolila clarify some of the mechanisms of animal behavior. According to Deutsch , obucheniezhivotnogo in the maze is not to develop a number of reactions , and in some установлениипоследовательности subtseley , alternate achievement of which leads kokonchatelnoy goal - the trough. There is no place training and regulation already vyuchennyhreaktsy . To explain this, Deitch has developed a hypothetical scheme based namotivatsionnoy model with feedback and using the principles of obschihprichinnyh factors , chain reactions and inhibitory connections . The importance of the principle of feedback notes in the study of a number of researchers biogeotsenologiiotmechayut . For the study of the brain are important methods of classical physiology of higher nervnoydeyatelnosti , morfofiziologii , electrophysiology , biochemistry , etc. However vozniklapotrebnost new methods that reveal the activity of the brain with a side - to tochkizreniya patterns of management and information processing . Attempts to study the brain of the system are not new. More NM Sechenov put zadachuvskryt essence mechanism of brain activity by finding the underlying principles etoydeyatelnosti . They opened one of them - the principle of reflexes. Pavlov, IP management principles explored the dynamics of higher neural centers , analysis and synthesis of signals coming from the outside , and showed what osobennostideyatelnosti brain in various states of the latter. The teaching of and research activities mozgaobogatili Anokhin . According to I. Kochergin, "to study the brain as a complex function of national importance sistemyvazhnoe modeling tool, allowing reveal the structure of the brain, neurons form connections and various parts of the brain together, neyronnoyorganizatsii principles , patterns of processing , transmission, storage, coding and information vmozge etc. "The use of computer modeling in the brain allows otrazhatprotsessy in their dynamics , but this method in this application has its strengths islabye side. In addition to the common features inherent in the brain and simulating its rabotuustroystvu , such as: - Material - natural character of all processes - some of the common forms of motion - a reflection - belonging to klassusamoorganizuyu -ing dynamical systems, which are laid : - The principle of feedback; - Structural and functional similarity ; - The ability to store information there are significant differences , such as the simulator is inherent only in lower forms of movement - the physical , chemical , and also the brain - the social , biological , reflection process in the brain of man is manifested in the subjective- soznatelnomvospriyatii external influences. Thinking is the result vzaimodeystviyasubekta knowledge with the object in a social environment , in the language of man and machine . Human language is conceptual in nature. Properties of objects and phenomena summarized by means of language . Modeliruyuscheeustroystvo deals with electrical pulses , which are assigned to man sbukvami , numbers. Thus , the machine , "says" not on the conceptual language , and sistemepravil , which by its nature is a formal , not having predmetnogosoderzhaniya . The use of mathematical methods in the analysis of the processes of the brain otrazhatelnoydeyatelnosti was made possible thanks to some of the assumptions formulated by McCulloch and Pitts . They are based on abstraction from svoystvestestvennogo neuron , the nature of metabolism , etc. is considered a neuron chistofunktsionalnoy side. Existing models that mimic the activity of the brain ( Farley , Clark , Neumann Kombertsona , Walter , George , Shannon , Uttley , Berl , etc.) diverted from the qualitative specificity of the natural neurons. However, in terms zreniyaizucheniya the functional side of the brain it is insignificant . In the literature, there are a number of approaches to the study of brain activity : • theory of automatic control ( living systems are considered kachestvesvoeobraznogo ideal object ) ; • Information ( replaces energy approach ) it osnovnyeprintsipy : - Selection of information links within the system ; - Allocation of the signal from the noise ; - Probabilistic. The successes obtained in the study of brain activity in the information aspect naosnove simulation , according to NM Amoz , have created the illusion that problemazakonomernostey functioning of the brain can only be solved with the help of etogometoda . However , in his opinion , any model is associated with a simplification , in particular: • Not all functions and specific characteristics are taken into account ; • distraction from the social , neurodynamic character. Thus , the conclusion of a critical attitude toward this method ( nelzyapereotsenivat its possibilities, but at the same time , it must be widely used In the Data area , subject to reasonable limitations ) .