Comparison of reverse-engineering methods using an in Silico network
Comparison of reverse-engineering methods using an in Silico network
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DOI：
10.1196/annals.1407.006
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发表时间：
2007-01-01
期刊：
影响因子：
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通讯作者：
Laubenbacher, Reinhard
中科院分区：
文献类型：
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作者：
Camacho, Diogo;Licona, Paola Vera;Laubenbacher, Reinhard
生物化学网络的逆向工程是系统生物学的核心问题。近年来，已经为此目的开发了几种方法，使用来自各个领域的技术。对不同方法的系统比较因其对数据的要求差异很大而变得复杂，从而难以制定基准。此外，由于缺乏关于大多数真实的网络的详细知识，因此不容易将实验数据用于此目的。本文包含了四个逆向工程方法的比较，使用模拟网络的数据。该网络足够真实和复杂，包括来自真实的网络的数据所带来的许多挑战。我们的研究结果表明，这两种方法的基础上遗传扰动的网络优于其他方法，包括动态贝叶斯网络和偏相关方法。
The reverse engineering of biochemical networks is a central problem in systems biology. In recent years several methods have been developed for this purpose, using techniques from a variety of fields. A systematic comparison of the different methods is complicated by their widely varying data requirements, making benchmarking difficult. Also, because of the lack of detailed knowledge about most real networks, it is not easy to use experimental data for this purpose. This paper contains a comparison of four reverse-engineering methods using data from a simulated network. The network is sufficiently realistic and complex to include many of the challenges that data from real networks pose. Our results indicate that the two methods based on genetic perturbations of the network outperform the other methods, including dynamic Bayesian networks and a partial correlation method.