Inference of Vohradský's models of genetic networks by solving two-dimensional function optimization problems.
Inference of Vohradský's models of genetic networks by solving two-dimensional function optimization problems.
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DOI：
10.1371/journal.pone.0083308
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发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Okada-Hatakeyama M
中科院分区：
文献类型：
--
作者：
Kimura S;Sato M;Okada-Hatakeyama M
遗传网络的推理是从基因表达水平的时间序列中推断出基因之间相互作用的问题。虽然已经提出了许多模型来描述遗传网络，但本研究侧重于Vohradský提出的数学模型。由于其优越的特点，一些研究者提出了基于Vohradský模型的推理方法。然而，当试图分析由数十个基因组成的大规模网络时，这些方法必须解决高维非线性函数优化问题。为了解决Vohradský模型参数估计困难的问题，本文提出了一种将问题定义为若干二维函数优化问题的新方法。通过对人工遗传网络推理问题的数值实验表明，虽然该方法的计算时间不是最短的，但在足够短的计算时间内，该方法能够更有效地估计Vohradský模型的参数。本研究将所提出的方法应用于细菌SOS DNA修复系统的实际推理问题，并成功地找到了几个合理的规律。
The inference of a genetic network is a problem in which mutual interactions among genes are inferred from time-series of gene expression levels. While a number of models have been proposed to describe genetic networks, this study focuses on a mathematical model proposed by Vohradský. Because of its advantageous features, several researchers have proposed the inference methods based on Vohradský's model. When trying to analyze large-scale networks consisting of dozens of genes, however, these methods must solve high-dimensional non-linear function optimization problems. In order to resolve the difficulty of estimating the parameters of the Vohradský's model, this study proposes a new method that defines the problem as several two-dimensional function optimization problems. Through numerical experiments on artificial genetic network inference problems, we showed that, although the computation time of the proposed method is not the shortest, the method has the ability to estimate parameters of Vohradský's models more effectively with sufficiently short computation times. This study then applied the proposed method to an actual inference problem of the bacterial SOS DNA repair system, and succeeded in finding several reasonable regulations.
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