Cytoscape: A Modeling Platform for Biomolecular Networks

Cytoscape：生物分子网络建模平台

• 批准号: 10166303
• 负责人: Trey Ideker
• 金额: $ 17.95万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-22 至 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10166303
• 关键词: 2019-nCoV; Academia; Address; Automation; Award; Basic Science; Big Data; Bioinformatics; Biological; Biology; COVID-19; Cells; Classification; Clinical; Clinical Data; Clinical Research; Cloud Computing; Code; Collaborations; Communities; Computer software; Computing Methodologies; Custom; Data; Data Analyses; Data Science; Development; Diagnosis; Disease; Disease Outcome; Documentation; Ecosystem; Ensure; Environment; Genes; Genetic; Goals; Human; Human Genetics; Human Genome; Immune response; Individual; Industry; Infection; International; Knowledge; Maintenance; Methods; Modeling; Modernization; Molecular; Molecular Genetics; Neighborhoods; Network-based; Outcome; Pathway Analysis; Pathway interactions; Patients; Population; Population Analysis; Population Genetics; Positioning Attribute; Process; Proteins; Provider; Publishing; Recommendation; Research; Research Personnel; Resources; Risk stratification; Series; Services; Software Tools; System; Techniques; Testing; Therapeutic; Time; Translating; United States National Institutes of Health; Update; Variant; Visualization software; base; biobank; clinical decision support; clinical decision-making; cloud based; cohort; comorbidity; data tools; data warehouse; disorder subtype; genetic analysis; genetic variant; genome wide association study; genomic data; human disease; improved; improved outcome; industry partner; infancy; large datasets; malignant breast neoplasm; model development; network models; open source; precision medicine; programs; research and development; responders and non-responders; response; success; tool; user-friendly; web services; web site

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.

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。