Bioinformatics Group

生物信息学组

• 批准号: 9927582
• 负责人: Petra LeBeau
• 金额: $ 47.65万
• 依托单位: RHO FEDERAL SYSTEMS DIVISION, INC.
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-01 至 2022-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9927582
• 关键词: Area; Bioinformatics; Biological; Biological Assay; Biological Sciences; Clinical; Communities; Complex; Consumption; DNA sequencing; Data; Data Set; Databases; Development; Dimensions; Disease; Ecosystem; Emerging Technologies; Engineering; Ensure; Experimental Designs; Fostering; Funding; Goals; High Performance Computing; Information Systems; Information Technology; Infrastructure; Investigation; Lab-On-A-Chips; Mass Spectrum Analysis; Mathematics; Measures; Meta-Analysis; Metadata; NMR Spectroscopy; National Institute of Allergy and Infectious Disease; Pattern; Play; Privatization; Process; Property; Proteome; Reproducibility of Results; Research; Research Personnel; Role; Structure; System; Techniques; Technology; Time; U-Series Cooperative Agreements; United States National Institutes of Health; Variant; biological systems; chromatin immunoprecipitation; data access; data dissemination; data exchange; data management; data quality; data sharing; data standards; experience; experimental study; high dimensionality; metabolome; microbiome; multidimensional data; programs; public repository; quality assurance; rho; sound; statistics; tool; transcriptome; transmission process; whole genome

PROJECT SUMMARY/ABSTRACT—BIOINFORMATICS GROUP The scale of research in the life sciences is increasing rapidly, due in part to the growing ubiquity of “omics”. High-throughput and high-dimensional assay technologies, including variations of DNA sequencing, array/lab-on-a-chip assays, mass spectrometry, nuclear magnetic resonance spectroscopy, and other technologies, allow investigators to study entire genomes, transcriptomes, proteomes, metabolomes, microbiomes, and other large-scale systems. Researchers examine biological systems holistically, looking for patterns and emergent properties or simply cast a wide net by measuring many more variables simultaneously in an experiment. DAIT-funded investigators are increasingly using these approaches. Advances in information technology also drive the increasing scale of research by facilitating the creation, sharing, pooling, and analysis of large databases of research data. Bioinformatics meets these scalability opportunities and challenges by applying techniques from computing, statistics, mathematics, and engineering to the management, analysis, and dissemination of large and or complex biological data sets. The Bioinformatics Group (BG) will serve as a core component of the DAIT Statistical and Clinical Coordinating Center and will help maximize the value of data collected by DAIT-sponsored clinical and mechanistic investigators by fostering long-term capacity for data sharing and utilization by the general research community. Building on Rho's extensive experience as a Statistical and Clinical Coordinating Center for a number of NIH and DAIT research networks, the BG will play a role in every stage of the data lifecycle: During study planning the BG will provide expert guidance to investigators on experimental design, emerging technologies, and analytical approaches, particularly with regards to the application of omics and other high- dimensional data types. The team will collaborate with investigators and other bioinformatics organizations to develop data standards for clinical and mechanistic data and apply those to DAIT study data sets and information systems developed by the center. Implementing these standards will ensure that data are consistently structured and annotated and will make them more easily shared and pooled. The BG will provide tools, high performance computing infrastructure, and analytical support for high-throughput and high- dimensional data sets. Finally, it will serve as the primary conduit for data dissemination from supported DAIT programs through the development of study portals for live data access and transfer of final study data sets to public repositories, such as ImmPort and TrialShare.

项目总结/摘要-生物信息学组 生命科学研究的规模正在迅速扩大，部分原因是生物技术的日益普及。 “omics”。高通量和高维分析技术，包括DNA测序的变化， 阵列/芯片实验室分析、质谱分析、核磁共振光谱分析等 技术，使研究人员能够研究整个基因组，转录组，蛋白质组，代谢组， 微生物组和其他大规模系统。研究人员全面检查生物系统，寻找 或者简单地通过同时测量更多的变量来撒一张大网 在一项实验中。DAIT资助的调查人员越来越多地使用这些方法。先进的信息 技术还通过促进创造、共享、汇集和分析，推动研究规模不断扩大 大型数据库的研究数据。生物信息学满足这些可扩展性的机会和挑战， 将计算、统计、数学和工程技术应用于管理、分析、 以及大型和/或复杂生物数据集的传播。 生物信息学小组（BG）将作为DAIT统计和临床研究的核心组成部分， 协调中心，并将有助于最大限度地发挥DAIT申办的临床和 机械调查员通过培养长期的数据共享能力和一般 研究社区。基于Rho作为统计和临床协调中心的丰富经验 对于一些NIH和DAIT研究网络，BG将在数据生命周期的每个阶段发挥作用： 在研究计划期间，BG将为研究者提供有关实验设计的专家指导， 技术和分析方法，特别是关于组学和其他高 多维数据类型。该团队将与研究人员和其他生物信息学组织合作， 制定临床和机制数据的数据标准，并将其应用于DAIT研究数据集， 中心开发的信息系统。实施这些标准将确保数据 一致的结构和注释，并将使它们更容易共享和汇集。BG将提供 工具、高性能计算基础设施，以及对高吞吐量和高 维度数据集。最后，它将作为从所支持的DAIT传播数据的主要渠道 通过开发实时数据访问和最终研究数据集传输的研究门户网站， 公共存储库，如ImmPort和TrialShare。