1] Department of Genetics and Genomic Sciences, New York, New York, USA. [2] Icahn Institute for Genomics and Multiscale Biology, New York, New York, USA. [3] Icahn School of Medicine at Mount Sinai, New York, New York, USA.
1] Icahn School of Medicine at Mount Sinai, New York, New York, USA. [2] Graduate School of Biomedical Sciences, New York, New York, USA.
Nat Immunol. 2014 Feb;15(2):118-27. doi: 10.1038/ni.2787.
The immune system is a highly complex and dynamic system. Historically, the most common scientific and clinical practice has been to evaluate its individual components. This kind of approach cannot always expose the interconnecting pathways that control immune-system responses and does not reveal how the immune system works across multiple biological systems and scales. High-throughput technologies can be used to measure thousands of parameters of the immune system at a genome-wide scale. These system-wide surveys yield massive amounts of quantitative data that provide a means to monitor and probe immune-system function. New integrative analyses can help synthesize and transform these data into valuable biological insight. Here we review some of the computational analysis tools for high-dimensional data and how they can be applied to immunology.
免疫系统是一个高度复杂和动态的系统。从历史上看，最常见的科学和临床实践一直是评估其各个组成部分。这种方法并不总能揭示控制免疫系统反应的相互连接的途径，也不能揭示免疫系统如何在多个生物系统和尺度上发挥作用。高通量技术可用于在全基因组范围内测量免疫系统的数千个参数。这些系统范围的调查产生了大量的定量数据，为监测和探测免疫系统功能提供了一种手段。新的综合分析可以帮助综合和转化这些数据，转化为有价值的生物学见解。在这里，我们回顾了一些用于高维数据的计算分析工具，以及它们如何应用于免疫学。
