Computational Modeling Core

项目总结（见说明）： 计算建模核心（CMC）的目标是通过迭代计算和实验方法开发病毒发病机制的预测模型。我们的系统病毒学计划将在人类和动物模型系统中的感染过程中为多个宿主组织系统生成转录组学（mRNA和miRNA），蛋白质组学，脂质组学和代谢组学数据。CMC将通过为实验设计，数据处理和预测建模的各个方面提供计算专业知识来为该计划做出贡献。我们拥有一个多学科团队，拥有生物信息学，统计学和机械建模方面的专业知识，可提供集成的功能工具箱来支持核心目标。 我们的计划利用了研究项目，技术核心和建模人员之间正在进行的，已建立的合作，以及流感病毒感染的大量现有数据。我们将利用这些数据和我们的专业知识，扩大我们对埃博拉和西尼罗河病毒感染的发病机制的调查。具体而言，竞争管理委员会的目标是： 通过差异表达的统计学评价，确定并量化病毒感染开始和进展期间宿主反应途径的变化。 比较和对比不同病毒病原体感染的宿主组织中激活的途径，并具体确定参与致病性的途径。 开发数学模型，定量预测动态宿主-病原体相互作用。 利用这些模型来识别可以通过治疗干预来操纵的宿主-病毒相互作用的新的紧急特性。 我们正在进行的项目的更新将用新的数据类型（miRNA，磷酸蛋白质组学，脂质组学和代谢组学）来增强现有数据，并提供宿主反应途径的机制建模和虚拟组织建模。

PROJECT SUMMARY (See instructions): The objective of the Computational Modeling Core (CMC) is to develop predictive models of viral pathogenesis through iterative computational and experimental approaches. Our Systems Virology program will generate transcriptomic (mRNA & miRNA), proteomic, lipidomic and metabolomic data for multiple host tissue systems over at time course of infection in both human and animal model systems. The CMC will contribute to the program by providing computational expertise for all aspects of experimental design, data processing and predictive modeling. We have a multi-disciplinary team with expertise in bioinformatics, statistics and mechanistic modeling to provide an integrated toolbox of capabilities to support the Core goals. Our program leverages ongoing, established collaborations between the research projects, technology cores, and modelers, as well as substantial existing data with Influenza virus infections. We will utilize these data and our expertise to extend our investigations into the pathogenesis of Ebola and West Nile virus infections. Specifically, the goals for the CMC are: To identify and quantify changes in host response pathways during initiation and progression of viral infection through statistical evaluation of differential expression. ¿ To compare and contrast pathways activated in host tissues infected by different viral pathogens and specifically identify those involved in pathogenicity. ¿ To develop mathematical models which quantitatively predict dynamical host-pathogen interactions. To utilize the models to identify novel emergent properties of host-virus interactions that can be manipulated through therapeutic intervention. The renewal of our ongoing program will augment existing data with new data types (miRNA, phosphoproteomics, lipidomics and metabolomics), as well as provide mechanistic modeling of host response pathways and virtual tissue modeling.