Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7435, USA.
Immunol Rev. 2013 Sep;255(1):256-74. doi: 10.1111/imr.12092.
Immunity to respiratory virus infection is governed by complex biological networks that influence disease progression and pathogenesis. Systems biology provides an opportunity to explore and understand these multifaceted interactions based on integration and modeling of multiple biological parameters. In this review, we describe new and refined systems-based approaches used to model, identify, and validate novel targets within complex networks following influenza and coronavirus infection. In addition, we propose avenues for extension and expansion that can revolutionize our understanding of infectious disease processes. Together, we hope to provide a window into the unique and expansive opportunity presented by systems biology to understand complex disease processes within the context of infectious diseases.
呼吸道病毒感染的免疫由影响疾病进展和发病机制的复杂生物网络控制。系统生物学提供了一个机会，可以基于多个生物学参数的整合和建模来探索和理解这些多方面的相互作用。在这篇综述中，我们描述了新的和改进的基于系统的方法，用于在流感和冠状病毒感染后对复杂网络中的新型靶标进行建模、识别和验证。此外，我们还提出了扩展和扩展的途径，可以彻底改变我们对传染病过程的理解。总的来说，我们希望提供一个窗口，了解系统生物学在传染病背景下理解复杂疾病过程所带来的独特而广阔的机会。
