Maintaining optimal state probabilities in biological systems |
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Authors: | Madhumita Ghosh Basant K Tiwary Dilip Datta |
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Institution: | (1) Department of Life Sciences, Assam University, Silchar, Assam, 788 011, India;(2) Department of Mechanical Engineering, National Institute of Technology, Silchar, Assam, 788 010, India |
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Abstract: | A biological problem is usually studied experimentally by reducing it into a number of modules. In contrast, the systems biology
approach seeks to address the collective behavior of interacting molecules vis-a-vis the corresponding higher level behavior.
Various attributes of a biological system are conditionally dependent on each other, and these conditionalities are usually
represented through Bayesian networks for computing easily the joint probability for a state of an attribute. In this article,
a genetic algorithm is investigated to a biological system, by representing it through a Bayesian network, for evaluating
the optimum state probabilities of different attributes, in order to obtain a desired joint probability for a given state
of an attribute. We believe that such a study would be helpful in achieving a desired health condition by maintaining various
attributes of a system to their estimated optimum levels. |
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Keywords: | Systems biology Bayesian network State probability Joint probability Genetic algorithm |
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