Centralized data management and analysis facilities

集中数据管理和分析设施

• 批准号: 394775100
• 负责人: Professor Dr. Dirk Isbrandt
• 金额: --
• 依托单位: Luxembourg Centre for Systems Biomedicine (LCSB)
• 依托单位国家: 德国
• 项目类别: Research Units
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/394775100?language=en
• 关键词: Centralized; data; management; analysis; facilities

This project is concerned with providing research data management services to scientists in the RU by harmonizing phenotype information, providing a central reference point for research results and bulk standardized processing of exome data. Integration of diverse data sets is key to the genetics projects (P1-P3), which will be primarily supported through standardized pipelines. The functional projects P4-P8 will be supported through software solutions for research collaboration and experimental planning with respect to data flow and formats. By providing crucial data management support, this project will ensure standardized data handling and will assist in arriving at valid research findings in the other projects. Research data management was performed by scientists the day they started collecting specimens and exchanging findings with their peers. The digital age brought many new technologies for measurements but thereby enhanced the data in volume and variety which complicated scientific studies. Large and heterogeneous data sources, which are typical for today’s biomedical research in general. This RU will produce and analyze DNA and RNA sequences beyond a Petabyte in bulk, but also functional and imaging as well as clinical data which requires a dedicated management for storing, processing, archiving and exchanging data to avoid inconsistencies and biases in advance.

该项目旨在通过协调表型信息、为研究结果提供中心参考点和外显子组数据的大量标准化处理，为RU科学家提供研究数据管理服务。整合各种数据集是遗传学项目（P1-P3）的关键，这些项目将主要通过标准化管道得到支持。功能项目P4-P8将通过软件解决方案在数据流和格式方面进行研究合作和实验规划。通过提供关键的数据管理支持，该项目将确保标准化的数据处理，并将有助于在其他项目中得出有效的研究结果。研究数据管理是由科学家开始收集标本并与同行交换发现的那一天开始的。数字时代带来了许多新的测量技术，但由此增加了数据的数量和种类，使科学研究复杂化。大而异构的数据源，这是当今生物医学研究的典型特征。该RU将批量生成和分析超过pb的DNA和RNA序列，还可以生成功能和成像以及临床数据，这些数据需要专门的管理来存储、处理、归档和交换数据，以提前避免不一致和偏差。