首页> 美国卫生研究院文献>Cold Spring Harbor Perspectives in Biology >Will Systems Biology Deliver Its Promise and Contribute to the Development of New or Improved Vaccines?: What Really Constitutes the Study of Systems Biology and How Might Such an Approach Facilitate Vaccine Design
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Will Systems Biology Deliver Its Promise and Contribute to the Development of New or Improved Vaccines?: What Really Constitutes the Study of Systems Biology and How Might Such an Approach Facilitate Vaccine Design

机译:系统生物学将提供其承诺并有助于开发新的或改进的疫苗?:真正构成了对系统生物学的研究以及这种方法如何促进疫苗设计的研究

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摘要

A dichotomy exists in the field of vaccinology about the promise versus the hype associated with application of “systems biology” approaches to rational vaccine design. Some feel it is the only way to efficiently uncover currently unknown parameters controlling desired immune responses or discover what elements actually mediate these responses. Others feel that traditional experimental, often reductionist, methods for incrementally unraveling complex biology provide a more solid way forward, and that “systems” approaches are costly ways to collect data without gaining true insight. Here I argue that both views are inaccurate. This is largely because of confusion about what can be gained from classical experimentation versus statistical analysis of large data sets (bioinformatics) versus methods that quantitatively explain emergent properties of complex assemblies of biological components, with the latter reflecting what was previously called “physiology.” Reductionist studies will remain essential for generating detailed insight into the functional attributes of specific elements of biological systems, but such analyses lack the power to provide a quantitative and predictive understanding of global system behavior. But by employing (1) large-scale screening methods for discovery of unknown components and connections in the immune system (omics), (2) statistical analysis of large data sets (bioinformatics), and (3) the capacity of quantitative computational methods to translate these individual components and connections into models of emergent behavior (systems biology), we will be able to better understand how the overall immune system functions and to determine with greater precision how to manipulate it to produce desired protective responses.
机译:关于与合理疫苗设计的“系统生物学”方法的应用相关的承诺与炒作的承诺存在二分法。有些人觉得它是有效地发现目前未知参数的唯一方法,控制所需的免疫应答或发现实际介导这些反应的内容。其他人觉得传统的实验性,通常还原剂,用于逐步解开复杂生物学的方法提供了更坚实的前进方式,“系统”方法是收集数据的昂贵方式,而不会获得真正的洞察力。在这里,我认为这两个观点都不准确。这主要是因为关于从古典实验中获得的困惑,与大数据集(生物信息学)的统计分析(生物信息学)与方法中的统计分析,这些方法是定量解释生物成分复杂组件的紧急性质,后者反映了以前称为“生理学”的内容。还原剂研究对于生成对生物系统的特定要素的功能属性的详细洞察,但这种分析缺乏提供对全球系统行为的定量和预测理解的权力。但是通过使用(1)大规模筛选方法,用于发现免疫系统中未知组件和连接(OMICS),(2)大数据集(生物信息学)的统计分析,以及(3)定量计算方法的容量将这些单独的组件和连接转化为紧急行为的模型(系统生物学),我们将能够更好地了解整体免疫系统如何运作,并以更高的精确确定如何操纵它以产生所需的保护响应。

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