Multi-cellular and multi-scale systems modeling to understand the dynamics of the human immune system in interdisciplinary applications

项目摘要/摘要 免疫系统可以说是仅次于大脑的第二复杂的人类系统。它的 对外界刺激的适当反应是由各种类型的网络式相互作用所支配的 细胞和细胞因子作为它们的通讯媒介。细胞间的复杂性 免疫系统的水平进一步恶化，因为类似复杂的生物学和 每个细胞内的生化网络(新陈代谢、基因调控等)对此负责 单细胞水平上的动力学和决策。这种多尺度的复杂性使它 要了解该病的完整病因和病理，具有难以置信的挑战性 免疫系统相关疾病。我的研究项目旨在确定免疫系统如何 系统可以整体重新布线，以诱导更高级别的决策，同时仍支持 系统在其他方面保持“健康”。为此，我的研究计划利用了高度的 跨学科研究团队(计算和实验免疫学家、软件 工程师、教育研究人员)和合作者共同构建虚拟免疫系统-- 多尺度、多方法的计算框架，以更好地理解复杂 免疫系统的动态特性，识别更准确的多维生物标记物， 并在合理的时间和成本内确定安全有效的治疗方法。在接下来的五年里 几年来，除了扩大虚拟免疫系统，我的项目还将继续发展 用于数据驱动的模型构建、可视化、计算 实时模拟和重复性，以推进免疫系统的多尺度建模 以及更远的地方。我们将继续破译各种不同情况下免疫系统的动态 CD_4~+T细胞在其自身环境下的病理变化及其可重程性 微环境。我的实验室将继续反复预测、验证和改进 使用系统方法和技术生成的预测。要做到这一点，我们将 生成我们的多组学数据以更准确地验证免疫系统行为并应用 我们的发现直接改进了计算方法。我的团队将继续建立 协作并深化我们现有的关系，包括与翻译合作伙伴 推进我们系统工作对药物发现的影响，国际团队建模 新冠肺炎，并与病毒学家和免疫学家一起进一步验证我们的计算 实验性的预测。

PROJECT SUMMARY/ABSTRACT The immune system is arguably the second most complex human system after the brain. Its proper response to foreign stimuli is governed by network-like interactions among various types of cells and cytokines as their communication mediators. The complexity at the inter-cellular level of the immune system is further exacerbated by the similarly complex biological and biochemical networks within each cell (metabolism, gene regulation, etc.) responsible for the dynamics and decision-making at the single-cell level. Such multiscale complexity makes it incredibly challenging to understand the complete etiology and pathology of immune-system-related diseases. My research program aims to identify how the immune system can be rewired en masse to elicit higher-order decision-making while still enabling the system to remain otherwise “healthy.” To this end, my research program is leveraging a highly interdisciplinary research team (computational and experimental immunologists, software engineers, and education researchers) and collaborators to build a Virtual Immune System -- a multi-scale, multi-approach computational framework to understand better the complex dynamical nature of the immune system, identify more accurate multi-dimensional biomarkers, and identify safe and effective treatments within a reasonable time and cost. In the next five years, in addition to expanding the Virtual Immune system, my program will continue to develop methods and technologies for data-driven model construction, visualization, computation, real-time simulations, and reproducibility to advance multi-scale modeling of the immune system and beyond. We will continue to decipher the dynamics of the immune system under various pathologies and the re-programmability of CD4+ T cells under the milieu of their microenvironments. My laboratory will continue to iteratively predict, validate, and refine predictions generated using the systems approaches and technologies. To do this, we will generate our multi-omics data to more precisely validate immune system behaviors and apply our findings to refine the computational approaches directly. My team will continue to build collaborations and deepen our existing relationships, including with translational partners to advance the impact of our systems work on drug discovery, the international team modeling COVID-19, and with virologists and immunologists to further validate our computational predictions experimentally.