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将糖组学数据引入语义网。

Introducing glycomics data into the Semantic Web.

作者信息

Aoki-Kinoshita Kiyoko F, Bolleman Jerven, Campbell Matthew P, Kawano Shin, Kim Jin-Dong, Lütteke Thomas, Matsubara Masaaki, Okuda Shujiro, Ranzinger Rene, Sawaki Hiromichi, Shikanai Toshihide, Shinmachi Daisuke, Suzuki Yoshinori, Toukach Philip, Yamada Issaku, Packer Nicolle H, Narimatsu Hisashi

机构信息

Research Center for Medical Glycoscience, National Institute of Advanced Industrial Science and Technology, Tsukuba Central-2, Umezono 1-1-1, Tsukuba 305-8568, Japan.

出版信息

J Biomed Semantics. 2013 Nov 26;4(1):39. doi: 10.1186/2041-1480-4-39.

Abstract

BACKGROUND

Glycoscience is a research field focusing on complex carbohydrates (otherwise known as glycans)a, which can, for example, serve as "switches" that toggle between different functions of a glycoprotein or glycolipid. Due to the advancement of glycomics technologies that are used to characterize glycan structures, many glycomics databases are now publicly available and provide useful information for glycoscience research. However, these databases have almost no link to other life science databases.

RESULTS

In order to implement support for the Semantic Web most efficiently for glycomics research, the developers of major glycomics databases agreed on a minimal standard for representing glycan structure and annotation information using RDF (Resource Description Framework). Moreover, all of the participants implemented this standard prototype and generated preliminary RDF versions of their data. To test the utility of the converted data, all of the data sets were uploaded into a Virtuoso triple store, and several SPARQL queries were tested as "proofs-of-concept" to illustrate the utility of the Semantic Web in querying across databases which were originally difficult to implement.

CONCLUSIONS

We were able to successfully retrieve information by linking UniCarbKB, GlycomeDB and JCGGDB in a single SPARQL query to obtain our target information. We also tested queries linking UniProt with GlycoEpitope as well as lectin data with GlycomeDB through PDB. As a result, we have been able to link proteomics data with glycomics data through the implementation of Semantic Web technologies, allowing for more flexible queries across these domains.

摘要

背景

糖科学是一个专注于复杂碳水化合物(又称聚糖)的研究领域,例如,聚糖可作为“开关”,在糖蛋白或糖脂的不同功能之间切换。由于用于表征聚糖结构的糖组学技术的进步,现在许多糖组学数据库都可公开获取,并为糖科学研究提供有用信息。然而,这些数据库几乎与其他生命科学数据库没有关联。

结果

为了最有效地为糖组学研究实现对语义网的支持,主要糖组学数据库的开发者就使用RDF(资源描述框架)表示聚糖结构和注释信息的最低标准达成了一致。此外,所有参与者都实现了该标准原型,并生成了其数据的初步RDF版本。为了测试转换后数据的实用性,所有数据集都上传到了Virtuoso三元组存储中,并测试了几个SPARQL查询作为“概念验证”,以说明语义网在跨原本难以实现的数据库进行查询方面的实用性。

结论

我们能够通过在单个SPARQL查询中链接UniCarbKB、GlycomeDB和JCGGDB成功检索信息,以获取我们的目标信息。我们还测试了通过PDB将UniProt与糖基表位以及凝集素数据与GlycomeDB链接的查询。结果,通过实施语义网技术,我们能够将蛋白质组学数据与糖组学数据链接起来,从而在这些领域进行更灵活的查询。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1269/4177142/4fc1e1b05ad9/2041-1480-4-39-1.jpg

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