Inference of S-system models of genetic networks using a cooperative coevolutionary algorithm
Inference of S-system models of genetic networks using a cooperative coevolutionary algorithm
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DOI：
10.1093/bioinformatics/bti071
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发表时间：
2005-04-01
期刊：
影响因子：
5.8
通讯作者：
Konagaya, A
中科院分区：
文献类型：
--
作者：
Kimura, S;Ide, K;Konagaya, A
动机：为了解决S系统模型中遗传网络推理问题的高维性，提出了问题分解策略。虽然这种策略确实显示出了希望，但当给定的时间序列数据包含测量噪声时，它不能提供一个容易适用于遗传网络的计算模拟的模型。鉴于我们对遗传网络的分析和理解依赖于计算模拟，这是问题分解的一个重大限制。结果：我们提出了一种推断大规模遗传网络的 S 系统模型的新方法。所提出的方法基于问题分解策略和协作共同进化算法。由于使用协作协同进化算法同时解决按问题分解策略划分的子问题，因此所提出的方法可用于推断任何可供计算模拟的 S 系统模型。为了验证所提出方法的有效性，我们将其应用于两个人工遗传网络推理问题。最后，所提出的方法用于分析实际的DNA微阵列数据。
Motivation: To resolve the high-dimensionality of the genetic network inference problem in the S-system model, a problem decomposition strategy has been proposed. While this strategy certainly shows promise, it cannot provide a model readily applicable to the computational simulation of the genetic network when the given time-series data contain measurement noise. This is a significant limitation of the problem decomposition, given that our analysis and understanding of the genetic network depend on the computational simulation.Results: We propose a new method for inferring S-system models of large-scale genetic networks. The proposed method is based on the problem decomposition strategy and a cooperative coevolutionary algorithm. As the subproblems divided by the problem decomposition strategy are solved simultaneously using the cooperative coevolutionary algorithm, the proposed method can be used to infer any S-system model ready for computational simulation. To verify the effectiveness of the proposed method, we apply it to two artificial genetic network inference problems. Finally, the proposed method is used to analyze the actual DNA microarray data.