Cytoscape: A Modeling Platform for Biomolecular Networks

此申请是针对NOT-HG-20-030提交的。我们将使用数据驱动的网络和 由Cytoscape生态系统工具和资源支持的分层建模技术，用于构建 SARS-CoV-2感染，并将使用这些模型来提出宿主反应的差异机制 群体遗传和新冠肺炎疾病结局数据分析。这些数据驱动的模型将提供 人口风险分层和潜在的新冠肺炎疗法的研究。我们的模型、分析结果和 将通过网站和数据储存库向研究界提供工具包。模特们将会是 派生自分子和遗传交互作用数据，将用于分析 英国生物库目前正在收集SARS-CoV-2感染、合并症和临床结果。这个 分析将随着每次数据发布而定期更新，从而维护最新的资源 研究社区。建模工具和管道将是用户友好的，并有良好的文档记录，使 研究人员需要建立替代模型或分析其他人口数据。

This application is being submitted in response to NOT-HG-20-030. We will use data-driven network and hierarchical modeling techniques enabled by Cytoscape ecosystem tools and resources to build models of SARS-CoV-2 infection and will use the models to propose mechanisms of variance in host response based on the analysis of population genetic and COVID-19 disease outcome data. These data-driven models will inform research in population risk stratification and potential COVID-19 therapies. Our models, analysis results, and toolset will be made available to the research community via a website and data repository. The models will be derived from molecular and genetic interaction data and will be used to analyze population data on SARS-CoV-2 infection, comorbidities, and clinical outcomes currently being collected by the UK BioBank. The analysis will be updated periodically with each release of data, maintaining an up-to-date resource for the research community. The modeling tools and pipelines will be user-friendly and well-documented, enabling researchers to build alternative models or to analyze other population data.