Data Management and Bioinformatics Core

数据管理和生物信息学核心项目摘要： 这一创新的集成系统生物学应用试图描绘复杂的宿主/病原体 发生在肺泡水平的相互作用，导致重症患者治疗失败 肺炎。尽管在这一领域进行了积极研究，但一种可以支持 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 有效的一般解决方案需要同时对所有生物学和医学进行建模。即使 一般的解决办法可能很难解决，但我们相信，通过集中精力可以取得实质性进展。 根据单一病症的临床、基因组和病原体数据，医院获得性肺炎(HAP)。 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，支持对HAP的系统生物学方法，并 广泛共享这些资源。DMBI核心将位于脚本的结合点，在那里它将提供 工具、方法、技能和基础设施，用于收集、集成、转换、分析和分发 两个项目产生的不同数据。DMBI核心的设计与实现是基于 假设以基因组为中心的方法和以表现组为中心的方法都是固有的 科学上的限制。相反，给予所有数据类型同等权重的系统生物学方法是 更有可能产生重大发现。要实现该项目更广泛的目标，将需要 临床数据与宿主和病原体的分子图谱数据的无缝集成。我们会 利用我们在整合电子病历和基因组数据方面的丰富经验，设计一种新的图表- 基于存储库。基因组数据的多种来源将与临床表型数据相结合 从填充重症监护患者电子病历的连续数据流中提取 单位。我们将利用在目标1中产生的数据集来进一步分析基因调控网络 使用新的计算工具和现有工具的新用途。特别是，我们将开发量身定制的- 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。将采取多管齐下的方式进行传播。 数据集和元数据将在适当的NIAID和/或NCBI档案中存档。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 安全、交互的Web门户将允许研究与研究数据存储库交互，以避免 不仅可以基于丰富的部分属性浏览和过滤数据，还可以直接运行分析。

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.