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首页> 外文期刊>BMC Systems Biology >Rapidly exploring structural and dynamic properties of signaling networks using PathwayOracle
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Rapidly exploring structural and dynamic properties of signaling networks using PathwayOracle

机译:使用PathwayOracle快速探索信令网络的结构和动态特性

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Background In systems biology the experimentalist is presented with a selection of software for analyzing dynamic properties of signaling networks. These tools either assume that the network is in steady-state or require highly parameterized models of the network of interest. For biologists interested in assessing how signal propagates through a network under specific conditions, the first class of methods does not provide sufficiently detailed results and the second class requires models which may not be easily and accurately constructed. A tool that is able to characterize the dynamics of a signaling network using an unparameterized model of the network would allow biologists to quickly obtain insights into a signaling network's behavior. Results We introduce PathwayOracle, an integrated suite of software tools for computationally inferring and analyzing structural and dynamic properties of a signaling network. The feature which differentiates PathwayOracle from other tools is a method that can predict the response of a signaling network to various experimental conditions and stimuli using only the connectivity of the signaling network. Thus signaling models are relatively easy to build. The method allows for tracking signal flow in a network and comparison of signal flows under different experimental conditions. In addition, PathwayOracle includes tools for the enumeration and visualization of coherent and incoherent signaling paths between proteins, and for experimental analysis – loading and superimposing experimental data, such as microarray intensities, on the network model. Conclusion PathwayOracle provides an integrated environment in which both structural and dynamic analysis of a signaling network can be quickly conducted and visualized along side experimental results. By using the signaling network connectivity, analyses and predictions can be performed quickly using relatively easily constructed signaling network models. The application has been developed in Python and is designed to be easily extensible by groups interested in adding new or extending existing features. PathwayOracle is freely available for download and use.
机译:背景技术在系统生物学中,向实验人员展示了用于分析信令网络动态特性的一系列软件。这些工具假定网络处于稳定状态,或者需要对目标网络进行高度参数化的模型。对于有兴趣评估信号在特定条件下如何通过网络传播的生物学家而言,第一类方法无法提供足够详细的结果,第二类方法可能需要无法轻松,准确地构建模型。能够使用网络的非参数化模型来表征信令网络动态的工具将使生物学家能够快速获得对信令网络行为的见识。结果我们引入了PathwayOracle,这是一套集成的软件工具套件,用于通过计算推断和分析信令网络的结构和动态特性。使PathwayOracle与其他工具区分开的功能是一种仅使用信号网络的连通性就可以预测信号网络对各种实验条件和刺激的响应的方法。因此,信令模型相对容易构建。该方法允许跟踪网络中的信号流并比较不同实验条件下的信号流。此外,PathwayOracle还包括用于枚举和可视化蛋白质之间相干和不相干信号通路的工具,以及用于进行实验分析的工具-在网络模型上加载和叠加实验数据(例如微阵列强度)。结束语PathwayOracle提供了一个集成的环境,在该环境中,可以快速进行信令网络的结构和动态分析,并可以与副实验结果一起可视化。通过使用信令网络连接,可以使用相对容易构建的信令网络模型快速执行分析和预测。该应用程序是使用Python开发的,旨在被有兴趣添加新功能或扩展现有功能的小组轻松扩展。 PathwayOracle可免费下载和使用。

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