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・ Evolutionary history of plants
・ Evolutionary Humanism
・ Evolutionary ideas of the Renaissance and Enlightenment
・ Evolutionary informatics
・ Evolutionary Informatics Lab
・ Evolutionary invasion analysis
・ Evolutionary landscape
・ Evolutionary leadership theory
・ Evolutionary linguistics
・ Evolutionary logic
・ Evolution Fight
・ Evolution Fresh
・ Evolution from Francis Turbine to Kaplan Turbine
・ Evolution Group
・ Evolution in Mendelian Populations
Evolution in Variable Environment
・ Evolution Mallorca International Film Festival
・ Evolution of a Filipino Family
・ Evolution of a Man
・ Evolution of a random network
・ Evolution of ageing
・ Evolution of biological complexity
・ Evolution of biparental care in tropical frogs
・ Evolution of birds
・ Evolution of brachiopods
・ Evolution of butterflies
・ Evolution of cells
・ Evolution of cephalopods
・ Evolution of cetaceans
・ Evolution of color vision


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Evolution in Variable Environment : ウィキペディア英語版
Evolution in Variable Environment

Evolution in Variable Environment (EVE) is a computer program designed to simulate microbial cellular behavior in various environments. The prediction of cellular responses is a rapidly evolving topic in systems biology and computational biology. The goal is to predict the behavior a particular organism in response to a set of environmental stimuli ''in silico''. Such predictions can have a significant impact on preventive medicine, biotechnology, and microbe re-engineering. Computational prediction of behavior has two major components: the integration and simulation of vast biological networks and the creation of external stimuli. Current limitations of the method are: lack of comprehensive experimental data on the various cellular subsystems and inadequate computational algorithms.
==Overview==
An organism that learns to modulate its behavior and gene expression based on temporal interrelationships between environmental factors possesses a competitive advantage of over other organisms that are unable to make such predictions. For example, learning when nutrients are going to be present in the environment allows the organism to selectively express genes that will take up the food source, thus allowing the organism to harvest energy.
Modeling these type of behaviors of even simple bacteria poses certain challenges. Given the diversity of biological systems, it would appear that the number of behavior responses to an environmental change would be nearly infinite. However, recent studies have shown that biological systems are optimized for a certain environment and will thus respond relatively specific ways to stimuli. This specificity simplifies the computations considerably.
The second challenge is the seemingly random environmental events. Ruling out circadian or temporal cycles, such as daytime versus nighttime or the different seasons, many events in the environment are unpredictable, such as weather patterns, water salinity, and oxygen levels. However, it turns out that certain environmental factors are coupled temporally. For example, an increase in water temperature is frequently correlated with an increase in water salinity. These relationships allow organisms to respond to specific environmental factors in a timely manner and thus increase their biological fitness.
The prediction of cellular responses bears considerable interest to scientists, physicians, and bio-engineers alike. For example, studying how a particular organism responds to external and internal stimuli can yield insights into the mechanisms of evolution. At the same time, such knowledge can also help physicians and health officials understand the infectious cycles of disease-causing bacteria and protists, allowing to them to establish preventive measures. Finally, knowing how bacteria behave under different stimuli may facilitate the development of engineered bacteria that perform certain functions, such as clearing oil spills. These examples are only some of the many applications of predicting behaviors.〔Balinga, N.S.. The Scale of Prediction. ''Science'' 320, 1297-1298 (2008)〕

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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