Consortium for Viral Systems Biology Modeling Core

项目总结/摘要 建模核心的目标是开发，验证和完善模型，以预测病原体遗传 和宿主免疫反应和生理特征影响病毒性出血热的存活和长期 拉沙病毒（LASV）和埃博拉病毒（EBOV）感染的后遗症。我们的多学科团队拥有专业知识 跨越统计思维、数学建模、进化生物学和计算， 免疫学分析、移动的传感器和临床数据。我们向病毒系统联盟提供 生物学核心和项目指导系统发育重建，以确定进化轨迹和 对LASV和EBOV宿主内变异体进行编目，对宿主决定簇进行遗传关联研究， 重要的是，就项目中实验设计的所有统计方面进行咨询。我们的首席创新官- 选择有三个方面。首先，我们将病毒序列进化纳入预测生存模型， 发展系统发育生存分析，以揭示宿主的病毒和宿主遗传决定因素 时间到事件的健康结果，同时适当控制共享的进化史和进化， 适应性免疫系统的发展。我们将大规模的非组学数据整合到这些生存数据中， 模型使用先进的计算技术，包括时间依赖的免疫和生理 无线患者监护仪和临床测试所产生的功能。第三，我们利用系统级预测 通过内部验证、生物学实验和 网络分析核心将提供有效的分析工具，使实时和脚本使用开放， 源，可复制的研究，并将马歇尔都动手短期课程和定期虚拟定量 诊所，以促进建模和实验之间的相互作用。

Project Summary/Abstract The Modeling Core targets the development, validation and refinement of models to predict pathogen genetic and host immune response and physiological features affecting viral hemorrhagic fever survival and long-term sequelae of Lassa virus (LASV) and Ebola virus (EBOV) infection. Our multidisciplinary team carries expertise across statistical thinking, mathematical modeling, evolutionary biology and computing to leverage sequenc- ing, immunological profiling, mobile sensor and clinical data. We provide to the Consortium for Viral Systems Biology Cores and Projects guidance in phylogenetic reconstruction to define evolutionary trajectories and cataloguing LASV and EBOV intra-host variants, genetic association studies mapping host determinants and, importantly, consultation on all statistical aspects of experimental design in the Projects. Our chief innova- tions are three-fold. First, we incorporate viral sequence evolution into predictive survival models through the development of phylogenetic survival analysis to uncover the viral and host genetic determinants of host time-to-event health outcomes while appropriately controlling for shared evolutionary history and incorporat- ing adaptive immunity repertoire development. We integrate large-scale non-omics data into these survival models using advancing computing technology to include time-dependent immunological and physiological features arising from wireless patient monitors and clinical tests. Third, we exploit systems-level prediction evaluation and refinement for iterative model building with internal validation, biological experimentation and network analysis. The Core will deliver effective analysis tools enabled for real-time and scriptable use in open- source, reproducible research and will marshall both hands-on short-courses and a regular virtual quantitative clinic to catalyze the interactions between modeling and experimentation.