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首页> 外文期刊>Journal of Integrative Bioinformatics >Using Data Warehouse Technology in Crop Plant Bioinformatics
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Using Data Warehouse Technology in Crop Plant Bioinformatics

机译:在农作物生物信息学中使用数据仓库技术

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Plant-specific data is managed in heterogeneous formats and is dispersed geographically. Based on this data, efficient analyses require a materialised integration, often realised with data warehouse technology today. We describe the requirements, problems and solution strategies for domain-crossing integration as the fundament for analysing plant biological data based on three current case studies. First, we introduce a system for retrieval of markers and mapping positions based on clustering of ESTs. The second case study illustrates the steps for diversity studies after genotyping a collection of about 3,000 ryegrass accessions (Lolium spp.), whereas in the third example data of approximately 250 barley cultivars (Hordeum vulgare) were used for associating haplotype- and SNP-patterns with malting parameters. For all case studies, we integrate data from different domains - sequence and marker data as well as IPK Genebank data including passport and phenotypic information. Specific problems associated with plant biological data and possible solution strategies are shown.
机译:特定于工厂的数据以异构格式进行管理,并且在地理上分散。基于这些数据,有效的分析需要具体的集成,而今天的数据仓库技术通常可以实现这种集成。我们基于三个当前的案例研究,描述了跨域集成的需求,问题和解决方案策略,作为分析植物生物学数据的基础。首先,我们介绍了一种基于EST聚类的标记和定位位置检索系统。第二个案例研究说明了对约3,000个黑麦草种(黑麦草)进行基因分型后进行多样性研究的步骤,而在第三个示例中,约250个大麦品种(大麦)的数据用于关联单倍型和SNP模式。与麦芽参数。对于所有案例研究,我们都整合了来自不同领域的数据-序列和标记数据以及包括护照和表型信息在内的IPK基因库数据。显示了与植物生物学数据相关的特定问题以及可能的解决方案。

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