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Expert curation for building network-based dynamical models: a case study on atherosclerotic plaque formation

机译:建立基于网络的动力学模型的专家策展:以动脉粥样硬化斑块形成为例

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摘要

Knowledgebases play an increasingly important role in scientific research, where the expert curation of biological knowledge in forms that are amenable to computational analysis (using ontologies for example)–provides a significant added value and enables new types of computational analyses for high throughput datasets. In this work, we demonstrate how expert curation can also play a more direct role in research, by supporting the use of network-based dynamical models to study a specific biological process. This curation effort is focused on the regulatory interactions between biological entities, such as genes or proteins and compounds, which may interact with each other in a complex manner, including regulatory complexes and conditional dependencies between co-regulators. This critical information has to be captured and encoded in a computable manner, which is currently far beyond the current capabilities of automatically constructed network. As a case study, we report here the prior knowledge network constructed by the sysVASC consortium to model the biological events leading to the formation of atherosclerotic plaques, during the onset of cardiovascular disease and discuss some specific examples to illustrate the main pitfalls and added value provided by the expert curation during this endeavor. >Database URL:
机译:知识库在科学研究中起着越来越重要的作用,在该领域中,以适合于计算分析的形式(例如使用本体论)对生物学知识进行专家管理可提供显着的附加值,并为高通量数据集提供新型的计算分析类型。在这项工作中,我们通过支持使用基于网络的动力学模型来研究特定的生物学过程,展示了专家策展如何在研究中发挥更直接的作用。这种管理工作的重点是生物实体(例如基因或蛋白质和化合物)之间的调节相互作用,这些相互作用可能以复杂的方式相互影响,包括调节复合物和协同调节剂之间的条件依赖性。必须以可计算的方式捕获和编码此关键信息,这目前远远超出了自动构建网络的当前功能。作为案例研究,我们在此报告由sysVASC联盟构建的先验知识网络,以对导致心血管疾病发作期间导致动脉粥样硬化斑块形成的生物学事件进行建模,并讨论一些具体示例以说明主要的陷阱和所提供的附加值在此过程中由专家策展。 >数据库网址

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