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Introduction |
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Topics of Interest |
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Submission Guidelines |
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Organisation |
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Introduction |
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Computational systems biology targets the computational modeling and analysis of biological processes on a systems level. On a systems level means that the nonlinear interaction between many heterogeneous and functionally diverse components is not ignored but captured on different levels of abstraction. It is expected that the holistic approach might require a less detailed simulation on the level of single functional elements. In any case, the level of abstraction will be governed by the task and sometimes it might be better to "ignore something of everything than everything of something".
Computational models are built in order to simulate biological systems, e.g. to verify their expected behaviour and to predict the behaviour if certain system constraints are changed. In order to predict unknown system responses, the model has to capture the essential system organisation and functionality. As is common in model building in any case the simpler model is to be preferred. Another important function of a model is its ability to teach us about the principles of the biological system. Since we are free to simplify and to adapt the model, we are possibly able to observe its bare essentials. This process is a prerequisite for the transfer of wanted properties of biological systems into other scientific domains where different basic system substrates hinder us to simply copy. Computational intelligence and systems engineering are examples, where we would like to transfer system level properties like robustness, flexibility and autonomy to.
Closely connected to the modelling, simulation and prediction of biological systems is the structural and functional analysis of experimental data on which in one way or another all models are based. The focus within the domain of computational systems biology is again more on the system level, thus on the data analysis of experimental findings on the networked interaction of many components. It is evident that organisational elements that relate structure to function play an essential role in this approach.
Besides advancing our understanding of biological processes, we can envisage at least two direct applications domains of computational systems biology: Medical practice and pharmaceutical industry, and computational intelligence. In both areas, a systems level understanding of the organisation of biological organisms seems to be required, in the first case to make qualitative steps towards new medications which treat the illness holistically, and in the second case towards artificial systems that are finally able to truly realize properties such as robustness, flexibility and autonomy. |
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Computational Systems Biology |
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A special session of the 2007 CEC |
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Important Dates:
Paper Submission: March, 31, 2007
Decision Notification: May 15, 2007
Camera-Ready Submission: June 15, 2007 |
