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Semantic Web-Based Integration of Cancer Pathways and Allele Frequency Data

机译:基于语义网络的癌症途径和等位基因频率数据整合

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We demonstrate the use of Semantic Web technology to integrate the ALFRED allele frequency database and the Starpath pathway resource. The linking of population-specific genotype data with cancer-related pathway data is potentially useful given the growing interest in personalized medicine and the exploitation of pathway knowledge for cancer drug discovery. We model our data using the Web Ontology Language (OWL), drawing upon ideas from existing standard formats BioPAX for pathway data and PML for allele frequency data. We store our data within an Oracle database, using Oracle Semantic Technologies. We then query the data using Oracle’s rule-based inference engine and SPARQL-like RDF query language. The ability to perform queries across the domains of population genetics and pathways offers the potential to answer a number of cancer-related research questions. Among the possibilities is the ability to identify genetic variants which are associated with cancer pathways and whose frequency varies significantly between ethnic groups. This sort of information could be useful for designing clinical studies and for providing background data in personalized medicine. It could also assist with the interpretation of genetic analysis results such as those from genome-wide association studies.
机译:我们演示了语义Web技术的使用,以整合ALFRED等位基因频率数据库和Starpath途径资源。鉴于对个性化医学的兴趣和对癌症药物发现的途径知识的利用日益增长,将特定人群的基因型数据与癌症相关的途径数据联系起来可能很有用。我们使用网络本体语言(OWL)对数据进行建模,并借鉴现有标准格式BioPAX(用于路径数据)和PML(用于等位基因频率数据)的思想。我们使用Oracle Semantic Technologies将数据存储在Oracle数据库中。然后,我们使用Oracle基于规则的推理引擎和类似SPARQL的RDF查询语言来查询数据。跨人群遗传学和途径领域进行查询的能力提供了回答许多与癌症相关的研究问题的潜力。在可能性中的能力是鉴定与癌症途径相关的遗传变体的能力,并且这些遗传变体在种族之间的差异很大。这种信息对于设计临床研究和提供个性化医学的背景数据可能有用。它还可以帮助解释遗传分析结果,例如来自全基因组关联研究的结果。

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