Modeling Core

建模核心

• 批准号: 10558422
• 负责人: DOUGLAS A LAUFFENBURGER
• 金额: $ 40.72万
• 依托单位: SCRIPPS RESEARCH INSTITUTE, THE
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-02-01 至 2028-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10558422
• 关键词: 2019-nCoV; Antibody titer measurement; Automobile Driving; Behavioral; Biological; Clinical; Cohort Studies; Collaborations; Communities; Community Outreach; Complex; Computer software; Computing Methodologies; Data; Data Set; Dimensions; Disease Outcome; Ebola; Epidemiology; Evolution; Experimental Designs; Goals; Immune; Immune response; Infection; Mathematics; Measurement; Methodology; Methods; Mission; Modality; Modeling; Molecular Epidemiology; Nature; Patient-Focused Outcomes; Phylogenetic Analysis; Predictive Factor; Preventive; Protocols documentation; Research; Research Personnel; Statistical Methods; System; Systems Biology; T-Lymphocyte; Techniques; Technology; Therapeutic; Training; Vaccination; Vaccines; Variant; Viral; Virus; computerized tools; data integration; fitness; fundamental research; heterogenous data; high dimensionality; insight; laboratory experiment; long-term sequelae; mathematical methods; model building; multidimensional data; multidisciplinary; outcome prediction; pathogen; pathogenic virus; prognostic; social; statistical and machine learning; supervised learning; tool; unsupervised learning; variants of concern

Project Summary - Modeling Core The Center for Viral Systems Biology (CViSB) collects and aggregates complex, multidimensional, and heterogeneous data, leading to challenges in interpreting these diverse experimental measurements. The Modeling Core’s primary goal is to develop and apply computational and statistical methods to elucidate key features of viral pathogens as well as host immune responses to infection and vaccination. Our approach will integrate data both within and across measurement modalities using data-driven mathematical tools to identify important host and virus factors, understand virus evolution and spread, and predict patient outcomes. We will disseminate our findings and tools, enabling CViSB as well as community researchers to perform similar analyses for a range of viral pathogens. To accomplish these objectives and support the overall mission of CViSB, we have the following four aims: (1) Build models to predict disease outcomes using data-driven latent variable models; (2) Develop methods to study host-pathogen dynamics by integrating heterogeneous data; (3) Construct methods for large-scale analysis of evolutionary dynamics; (4) Integrate social, environmental, and virus factors into models to understand virus variant spread; and (5) Provide broad analysis support for CViSB and the SysBio community.

项目摘要 - 建模核心 病毒系统生物学中心（CVISB）收集和聚集了复杂，多维和 异质数据，导致解释这些不同的实验测量的挑战。 建模Core的主要目标是开发和应用计算和统计方法以阐明 病毒病原体的关键特征以及对感染和疫苗接种的宿主免疫反应。我们的 方法将使用数据驱动的测量方式内和跨测量方式集成数据 数学工具识别重要的宿主和病毒因素，了解病毒的演变和扩散， 并预测患者的预后。我们将传播我们的发现和工具，使CVISB以及 社区研究人员对一系列病毒病原体进行类似的分析。 为了实现这些目标并支持CVISB的整体使命，我们有以下四个 目的：（1）建立模型，以使用数据驱动的潜在变量模型来预测疾病的结果； （2）发展 通过整合异质数据研究宿主 - 病原体动力学的方法； （3）构造方法 进化动力学的大规模分析； （4）将社会，环境和病毒因素整合到 了解病毒变体传播的模型； （5）为CVISB和 Sysbio社区。