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Inference of genetic networks using S-system

机译:使用S系统推断遗传网络

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In this paper we present an evolutionary approach for inferring the structure and dynamics in gene circuits from observed expression kinetics. For representing the regulatory interactions in a genetic network the decoupled S-system formalism has been used. We proposed an Information Criteria based fitness evaluation for model selection instead of the traditional Mean Squared Error (MSE) based fitness evaluation. A hill climbing local search method has been incorporated in our evolutionary algorithm for attaining the skeletal architecture which is most frequently observed in biological networks. Using small and medium-scale artificial networks we verified the implementation. The reconstruction method identified the correct network topology and predicted the kinetic parameters with high accuracy.
机译:在本文中,我们提出了一种从观察到的表达动力学推断基因回路的结构和动力学的进化方法。为了表示遗传网络中的调控相互作用,已使用解耦的S系统形式主义。我们提出了一种基于信息准则的适合度评估模型选择,而不是基于传统均方误差(MSE)的适合度评估。爬山局部搜索方法已被纳入我们的进化算法中,以获得在生物网络中最常观察到的骨骼结构。使用中小型人工网络,我们验证了该实现。该重构方法识别出正确的网络拓扑,并以较高的精度预测了动力学参数。

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