Reverse engineering validation using a benchmark synthetic gene circuit in human cells.
Reverse engineering validation using a benchmark synthetic gene circuit in human cells.
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DOI：
10.1021/sb300093y
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发表时间：
2013-05-17
影响因子：
4.7
通讯作者：
Bleris, Leonidas
中科院分区：
文献类型：
--
作者：
Kang, Taek;White, Jacob T.;Xie, Zhen;Benenson, Yaakov;Sontag, Eduardo;Bleris, Leonidas
多组分生物网络往往是不完全理解，在很大程度上是由于缺乏可靠和强大的网络逆向工程和表征方法。因此，开发自动化和严格验证的方法来解开人类细胞中生物分子网络的复杂性仍然是生命科学家和工程师的核心挑战。今天，当涉及到实验和分析要求时，逆向工程方法存在很大的多样性，这使得独立验证和比较其预测能力变得困难。在这项工作中，我们介绍了一个定制的实验平台，用于开发和验证哺乳动物细胞中的逆向工程和途径表征算法。具体来说，我们稳定地将合成基因网络整合到人类肾脏细胞中，并将其用作验证逆向工程方法的基准。该网络与内源性细胞信号正交，包含一小组可用于量化重建性能的调节相互作用。通过对网络的每个模块化组件进行连续扰动并比较蛋白质和RNA测量，我们研究了能够可靠地重建集成合成网络的因果关系的条件。
Multi-component biological networks are often understood incompletely, in large part due to the lack of reliable and robust methodologies for network reverse engineering and characterization. As a consequence, developing automated and rigorously validated methodologies for unraveling the complexity of biomolecular networks in human cells remains a central challenge to life scientists and engineers. Today, when it comes to experimental and analytical requirements, there exists a great deal of diversity in reverse engineering methods, which renders the independent validation and comparison of their predictive capabilities difficult. In this work we introduce an experimental platform customized for the development and verification of reverse engineering and pathway characterization algorithms in mammalian cells. Specifically, we stably integrate a synthetic gene network in human kidney cells and use it as a benchmark for validating reverse engineering methodologies. The network, which is orthogonal to endogenous cellular signaling, contains a small set of regulatory interactions that can be used to quantify the reconstruction performance. By performing successive perturbations to each modular component of the network and comparing protein and RNA measurements, we study the conditions under which we can reliably reconstruct the causal relationships of the integrated synthetic network.
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影响因子：
7.3
作者：
Prill RJ;Saez-Rodriguez J;Alexopoulos LG;Sorger PK;Stolovitzky G
通讯作者：
Stolovitzky G
影响因子：
2
作者：
Bruggeman, FJ;Westerhoff, HV;Kholodenko, BN
通讯作者：
Kholodenko, BN
影响因子：
7.3
作者：
Pezze, Piero Dalle;Sonntag, Annika G.;Thedieck, Kathrin
通讯作者：
Thedieck, Kathrin
DOI：
10.1073/pnas.0913357107
发表时间：
2010-04-06
影响因子：
11.1
作者：
Marbach, Daniel;Prill, Robert J.;Stolovitzky, Gustavo
通讯作者：
Stolovitzky, Gustavo
影响因子：
48
作者：
Marbach, Daniel;Costello, James C.;Kueffner, Robert;Vega, Nicole M.;Prill, Robert J.;Camacho, Diogo M.;Allison, Kyle R.;Kellis, Manolis;Collins, James J.;Stolovitzky, Gustavo
通讯作者：
Stolovitzky, Gustavo