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: 10330815
• 负责人: Tomas Helikar
• 金额: $ 37.13万
• 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/10330815
• 关键词: Behavior; Biochemical; Biological; Biological Markers; Biological Models; Brain; CD4 Positive T Lymphocytes; COVID-19; Cells; Cellular Metabolic Process; Collaborations; Communication; Communities; Complex; Computer software; Decision Making; Disease; Education; Etiology; Funding; Gene Expression Regulation; Human; Immune; Immune response; Immune system; Immunological Models; Immunologist; Interdisciplinary Study; International; Laboratories; Mediator of activation protein; Methods; Modeling; Multiomic Data; Nature; Pathology; Pharmacotherapy; Property; Reproducibility; Research; Research Personnel; Software Engineering; Stimulus; System; Technology; Time; Visualization; Work; cell type; computer framework; cost; cytokine; data-driven model; design; drug discovery; effective therapy; multi-scale modeling; pathogen; predictive modeling; programs; response; simulation; translational scientist; virtual

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.

项目总结/文摘