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

多细胞和多尺度系统建模，以了解跨学科应用中人体免疫系统的动态

• 批准号: 10799092
• 负责人: Tomas Helikar
• 金额: $ 24.74万
• 依托单位: UNIVERSITY OF NEBRASKA LINCOLN
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2026-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10799092
• 关键词: Biological; Biological Markers; Biological Models; Cells; Communication; Communities; Complex; Computer Models; Computer software; Data; Decision Making; Development; Dimensions; Disease; Education; Gene Expression Regulation; Human; Immune; Immune response; Immune system; Immunological Models; Immunologist; Infrastructure; Interdisciplinary Study; Mediator; Metabolism; Methods; Modeling; Nature; Property; Reproducibility; Research; Research Personnel; Signal Transduction; Software Engineering; System; Technology; Time; Visualization; Work; cell type; cloud based; computer framework; cost; data-driven model; effective therapy; human model; improved; knowledge integration; multi-scale modeling; parent grant; pathogen; predictive modeling; programs; simulation; translational scientist; virtual

Project Summary The parent grant, 2R35GM119770, (“Multi-cellular and multi-scale systems modeling to understand the dynamics of the human immune system in interdisciplinary applications”) supports my research program, which 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, we are 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. To this end, we have been building a comprehensive model of the immune system, that integrates knowledge and data across several scales of biological organization, including metabolism, gene regulation, signal transduction, and communication among the different types of immune cells. In addition to expanding the Virtual Immune system, my program continues 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, including a cloud-based collaborative modeling software, Cell Collective. This supplement will enable us to generate new high-quality data under consistent conditions that will be used to significantly improve the quality and accuracy of the Virtual Immune System model. The model, along with the data, will be made available to the community through our computing infrastructure.

项目摘要 母基金，2 R35 GM 119770，（“多细胞和多尺度系统建模，以了解动态的 人类免疫系统的跨学科应用”）支持我的研究计划，其目的是确定如何在人类免疫系统中的跨学科应用。 免疫系统可以被重新连接，以引发更高层次的决策，同时仍然使系统保持 否则就是“健康”为此，我们正在利用一个高度跨学科的研究团队（计算和 实验免疫学家，软件工程师和教育研究人员）和合作者建立一个虚拟免疫 系统-一个多尺度，多方法的计算框架，以更好地理解复杂的动力学性质， 免疫系统，识别更准确的多维生物标志物，并确定安全有效的治疗方法 在合理的时间和成本内。为此，我们一直在建立一个全面的免疫系统模型， 整合了生物组织的几个尺度上的知识和数据，包括新陈代谢，基因调控， 信号转导和不同类型免疫细胞之间的通信。除了扩大虚拟 免疫系统，我的项目继续开发数据驱动模型构建的方法和技术， 可视化、计算、实时模拟和再现性，以推进免疫系统的多尺度建模 系统和超越，包括基于云的协作建模软件，细胞集体。该补充将 使我们能够在一致的条件下生成新的高质量数据，这些数据将用于显著改善 虚拟免疫系统模型的质量和准确性。该模型，连同沿着的数据，将提供给 通过我们的计算基础设施。