首页> 外文会议>PSB;Pacific symposium on biocomputing; 20090105-09;20090105-09; Kohala Coast, HI(US);Kohala Coast, HI(US) >TOWARDS A CYTOKINE-CELL INTERACTION KNOWLEDGEBASE OF THE ADAPTIVE IMMUNE SYSTEM
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TOWARDS A CYTOKINE-CELL INTERACTION KNOWLEDGEBASE OF THE ADAPTIVE IMMUNE SYSTEM

机译:适应免疫系统的细胞因子与细胞相互作用的知识基础

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The immune system of higher organisms is, by any standard, complex. To date, using reductionist techniques, immunologists have elucidated many of the basic principles of how the immune system functions, yet our understanding is still far from complete. In an era of high throughput measurements, it is already clear that the scientific knowledge we have accumulated has itself grown larger than our ability to cope with it, and thus it is increasingly important to develop bioinformatics tools with which to navigate the complexity of the information that is available to us. Here, we describe ImmuneXpresso, an information extraction system, tailored for parsing the primary literature of immunology and relating it to experimental data. The immune system is very much dependent on the interactions of various white blood cells with each other, either in synaptic contacts, at a distance using cytokines or chemokines, or both. Therefore, as a first approximation, we used ImmuneXpresso to create a literature derived network of interactions between cells and cytokines. Integration of cell-specific gene expression data facilitates cross-validation of cytokine mediated cell-cell interactions and suggests novel interactions. We evaluate the performance of our automatically generated multi-scale model against existing manually eurated data, and show how this system can be used to guide experimentalists in interpreting multi-scale, experimental data. Our methodology is scalable and can be generalized to other systems.
机译:从任何标准来看,高级生物的免疫系统都是复杂的。迄今为止,免疫学家已经使用还原论技术阐明了免疫系统如何运作的许多基本原理,但我们的理解还远远不够。在高通量测量的时代,很明显,我们积累的科学知识本身已经超出了我们的能力,因此,开发生物信息学工具以导航信息的复杂性变得越来越重要。对我们可用。在这里,我们介绍ImmuneXpresso,这是一种信息提取系统,专门用于解析免疫学的主要文献并将其与实验数据相关联。免疫系统非常依赖于各种白细胞彼此之间的相互作用,或者通过突触接触,使用细胞因子或趋化因子在一定距离或两者兼而有之。因此,作为第一个近似值,我们使用ImmuneXpresso创建了文献衍生的细胞与细胞因子之间相互作用的网络。细胞特异性基因表达数据的整合促进了细胞因子介导的细胞-细胞相互作用的交叉验证,并提出了新颖的相互作用。我们将针对现有的手动剔除数据评估我们自动生成的多尺度模型的性能,并展示该系统如何用于指导实验学家解释多尺度的实验数据。我们的方法是可扩展的,可以推广到其他系统。

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