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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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Biomedical research has been revolutionized by highthroughputrntechniques and the enormous amount of biological datarnthey are able to generate. Genetic networks arise as an essentialrntask to mine these data since they explain the function of genes inrnterms of how they influence other genes. Many modelingrnapproaches have been proposed for building genetic networks up.rnHowever, it is not clear what the advantages and disadvantages ofrneach model are. There are several ways to discriminate networkrnbuilding models, being one of the most important whether the datarnbeing mined presents a static or dynamic fashion. In this work werncompare static and dynamic models over a problem related to therninflammation and the host response to injury. We show how bothrnmodels provide complementary information and cross-validate thernobtained results.
机译:高通量技术已彻底改变了生物医学研究,并且能够产生大量生物数据。遗传网络是挖掘这些数据的必不可少的任务,因为它们解释了基因的功能,无论它们如何影响其他基因。已经提出了许多用于建立遗传网络的建模方法。但是,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,我们比较了与炎症和宿主对损伤的反应有关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了获得的结果。

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