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Modeling Genetic Networks: Comparison of Static and Dynamic Models

机译:遗传网络建模:静态和动态模型的比较

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摘要

Biomedical research has been revolutionized by high-throughput techniques and the enormous amount of biological data they are able to generate. The interest shown over network models and systems biology is rapidly raising. Genetic networks arise as an essential task to mine these data since they explain the function of genes in terms of how they influence other genes. Many modeling approaches have been proposed for building genetic networks up. However, it is not clear what the advantages and disadvantages of each model are. There are several ways to discriminate network building models, being one of the most important whether the data being mined presents a static or dynamic fashion. In this work we compare static and dynamic models over a problem related to the inflammation and the host response to injury. We show how both models provide complementary information and cross-validate the obtained results.
机译:高通量技术及其能够生成的大量生物数据已经彻底改变了生物医学研究。对网络模型和系统生物学的兴趣正在迅速提高。遗传网络是挖掘这些数据的一项重要任务,因为它们从它们如何影响其他基因的角度解释了基因的功能。已经提出了许多用于建立遗传网络的建模方法。但是,尚不清楚每种模型的优缺点。有多种方法可以区分网络构建模型,这是要挖掘的数据呈现静态还是动态方式的最重要方法之一。在这项工作中,我们比较了关于炎症和宿主对损伤反应的问题的静态和动态模型。我们展示了两个模型如何提供补充信息并交叉验证所获得的结果。

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