Data Management and Bioinformatics Core

数据管理和生物信息学核心

• 批准号: 10326811
• 负责人: JUSTIN B. STARREN
• 金额: $ 31.7万
• 依托单位: NORTHWESTERN UNIVERSITY AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-01-17 至 2022-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10326811
• 关键词: Algorithms; Alveolar; Architecture; Archives; Area; Behavior; Big Data to Knowledge; Bioinformatics; Biology; Clinical; Clinical Data; Collection; Complex; Data; Data Science; Data Set; Data Storage and Retrieval; Disease; Funding Opportunities; Genome; Genomics; Goals; Graph; Infrastructure; Instruction; Intensive Care Units; Lead; Liquid substance; Medicine; Metadata; Methods; Modeling; Molecular; Molecular Profiling; Multiomic Data; National Institute of Allergy and Infectious Disease; Nosocomial pneumonia; Pathway interactions; Patients; Pneumonia; Precision Medicine Initiative; Proteomics; Research; Research Personnel; Resources; Running; Secure; Source; Systems Biology; Testing; United States National Institutes of Health; Universities; Weight; base; bioinformatics tool; biomedical informatics; clinical phenotype; computerized tools; computing resources; data dissemination; data management; data repository; data streams; design; diverse data; experience; gene regulatory network; genetic variant; genome wide association study; genomic data; genomic locus; innovation; multiscale data; novel; novel strategies; pathogen; phenome; phenomics; pneumonia treatment; repository; response; skills; tool; treatment response; web portal

Data Management and Bioinformatics Core Project Summary: This innovative integrated systems biology application seeks to delineate the complex host/pathogen interactions occurring at the alveolar level that lead to unsuccessful response to therapy in serious pneumonia. In spite of active research in this area, a generalize multi-scale solution that can support a systems biology approach to clinical problems remains elusive. This is not surprising, given that a general solution effectively requires modeling all of biology and medicine simultaneously. Even though a general solution may be intractable, we believe that substantial progress can be made by focusing on the clinical, genomic, and pathogen data for a single condition, Hospital Acquired Pneumonia (HAP). The overall goal of the Data Management and Bioinformatics (DMBI) Core is to develop and implement new and enhanced computational resources that support a systems biology approach to HAP, and to share those resources broadly. The DMBI Core will sit at the nexus of SCRIPT where it will provide the tools, methods, skills and infrastructure to collect, integrate, transform, analyze and distribute the diverse data generated by both projects. The design and implementation of the DMBI Core is based on the premise that genome-centric approaches and phenome-centric approaches are both inherently scientifically limiting. Rather, a systems biology approach that gives equal weight to all data types is more likely to produce significant findings. Achieving the broader goals of this project will require the seamless integration of clinical data with molecular profiling data on both host and pathogen. We will leverage our extensive experience in the integration of EHR and genomic data to design a novel graph- based repository. The multiple sources of genomic data will be integrated with clinical phenomic data extracted from the continuous stream of data that populates the EHR in patients in the intensive care unit. We will utilize the data sets generated in Aim 1 for further analysis of the gene regulatory networks using both novel computation tools and novel uses of existing tools. In particular, we will develop tailor- made algorithms for an integrative analysis of multiple omics data sets that enable modeling of the underlying gene regulatory networks. A multi-pronged approach to dissemination will be employed. Datasets and metadata will be archived in the appropriate NIAID and/or NCBI archives. Computational tools will be distributed through a GitHub repository. Of greater long term value will be the creation of a secure, interactive web portal that will allow research to interact with the study data repository to not only browse and filter data based on a rich section of attributes, but also to run analysis directly.

数据管理和生物信息学核心项目摘要： 这种创新的综合系统生物学应用旨在描述复杂的宿主/病原体 发生在肺泡水平的相互作用，导致严重的治疗反应失败 肺炎。尽管该领域的研究很活跃，但仍存在一种通用的多尺度解决方案，可以支持 解决临床问题的系统生物学方法仍然难以捉摸。这并不奇怪，因为 有效的通用解决方案需要同时对所有生物学和医学进行建模。虽然 一个普遍的解决方案可能是棘手的，我们相信通过集中精力可以取得实质性进展 医院获得性肺炎 (HAP) 单一病症的临床、基因组和病原体数据。 数据管理和生物信息学 (DMBI) 核心的总体目标是开发和实施 新的和增强的计算资源支持 HAP 的系统生物学方法，并 广泛共享这些资源。 DMBI 核心将位于 SCRIPT 的枢纽，在那里它将提供 收集、整合、转换、分析和分发信息的工具、方法、技能和基础设施 两个项目生成的不同数据。 DMBI核心的设计和实现基于 前提是以基因组为中心的方法和以表组为中心的方法本质上都是 科学限制。相反，对所有数据类型给予同等重视的系统生物学方法是 更有可能产生重大发现。实现该项目更广泛的目标需要 将临床数据与宿主和病原体的分子分析数据无缝集成。我们将 利用我们在 EHR 和基因组数据整合方面的丰富经验来设计一个新颖的图表 - 基于存储库。多种来源的基因组数据将与临床表组数据整合 从重症监护患者 EHR 中的连续数据流中提取 单元。我们将利用目标 1 中生成的数据集进一步分析基因调控网络 使用新颖的计算工具和现有工具的新颖用途。特别是，我们将开发定制 制定了对多个组学数据集进行综合分析的算法，从而能够对 潜在的基因调控网络。将采取多管齐下的传播方式。 数据集和元数据将存档在适当的 NIAID 和/或 NCBI 档案中。计算型 工具将通过 GitHub 存储库分发。更大的长期价值将是创造 一个安全的交互式门户网站，允许研究与研究数据存储库进行交互，而不是 不仅可以根据丰富的属性浏览和过滤数据，还可以直接运行分析。