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Minimum network constraint on reverse engineering to develop biological regulatory networks

机译:对开发生物监管网络的逆向工程的最小网络约束

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Reconstructing the topological structure of biological regulatory networks from microarray expression data or data of protein expression profiles is one of major tasks in systems biology. In recent years, various mathematical methods have been developed to meet this task. Here, based on our previously reported reverse engineering method, we propose a new constraint, i.e., the minimum network constraint, to facilitate the reconstruction of biological networks. Three well studied regulatory networks (the budding yeast cell cycle network, the fission yeast cell cycle network, and the SOS network of Escherichia coli) were used as the test sets to verify the performance of this method. Numerical results show that the biological networks prefer to use the minimal networks to fulfill their functional tasks, making it possible to apply minimal network criteria in the network reconstruction process. Two scenarios were considered in the reconstruction process: generating data using different initial conditions; and generating data from knock out and over-expression experiments. In both cases, network structures are revealed faithfully in a few steps using our approach. (C) 2015 Elsevier Ltd. All rights reserved.
机译:从微阵列表达数据或蛋白质表达谱数据重建生物调控网络的拓扑结构是系统生物学的主要任务之一。近年来,已经开发了各种数学方法来满足该任务。在此,根据我们先前报道的逆向工程方法,我们提出了一个新的约束条件,即最小网络约束条件,以促进生物网络的重建。使用三个经过充分研究的调节网络(芽孢酵母细胞周期网络,裂变酵母细胞周期网络和大肠杆菌的SOS网络)作为测试集,以验证该方法的性能。数值结果表明,生物网络更喜欢使用最小网络来完成其功能任务,从而有可能在网络重建过程中应用最小网络标准。在重建过程中考虑了两种情况:使用不同的初始条件生成数据;并从敲除和过表达实验中生成数据。在这两种情况下,使用我们的方法都可以在几个步骤中忠实地揭示网络结构。 (C)2015 Elsevier Ltd.保留所有权利。

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