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肝脏图谱:一个独特的综合知识数据库,用于肝脏和肝脏疾病的系统水平研究。

LiverAtlas: a unique integrated knowledge database for systems-level research of liver and hepatic disease.

机构信息

Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.

出版信息

Liver Int. 2013 Sep;33(8):1239-48. doi: 10.1111/liv.12173. Epub 2013 Apr 21.

DOI:10.1111/liv.12173
PMID:23601370
Abstract

BACKGROUND

A large amount of liver-related physiological and pathological data exist in publicly available biological and bibliographic databases, which are usually far from comprehensive or integrated. Data collection, integration and mining processes pose a great challenge to scientific researchers and clinicians interested in the liver.

METHOD

To address these problems, we constructed LiverAtlas (http://liveratlas.hupo.org.cn), a comprehensive resource of biomedical knowledge related to the liver and various hepatic diseases by incorporating 53 databases.

RESULTS

In the present version, LiverAtlas covers data on liver-related genomics, transcriptomics, proteomics, metabolomics and hepatic diseases. Additionally, LiverAtlas provides a wealth of manually curated information, relevant literature citations and cross-references to other databases. Importantly, an expert-confirmed Human Liver Disease Ontology, including relevant information for 227 types of hepatic disease, has been constructed and is used to annotate LiverAtlas data. Furthermore, we have demonstrated two examples of applying LiverAtlas data to identify candidate markers for hepatocellular carcinoma (HCC) at the systems level and to develop a systems biology-based classifier by combining the differential gene expression with topological features of human protein interaction networks to enhance the ability of HCC differential diagnosis.

CONCLUSION

LiverAtlas is the most comprehensive liver and hepatic disease resource, which helps biologists and clinicians to analyse their data at the systems level and will contribute much to the biomarker discovery and diagnostic performance enhancement for liver diseases.

摘要

背景

大量与肝脏相关的生理和病理数据存在于公开的生物和文献数据库中,这些数据通常不够全面或整合。数据收集、整合和挖掘过程对关注肝脏的科学研究人员和临床医生构成了巨大挑战。

方法

为了解决这些问题,我们通过整合 53 个数据库,构建了一个综合性的与肝脏和各种肝脏疾病相关的生物医学知识库——LiverAtlas(http://liveratlas.hupo.org.cn)。

结果

在目前的版本中,LiverAtlas 涵盖了与肝脏相关的基因组学、转录组学、蛋白质组学、代谢组学和肝脏疾病的数据。此外,LiverAtlas 还提供了大量人工整理的信息、相关文献引用和与其他数据库的交叉引用。重要的是,我们构建了一个经过专家确认的人类肝脏疾病本体,其中包含了 227 种肝脏疾病的相关信息,用于注释 LiverAtlas 数据。此外,我们还展示了两个应用 LiverAtlas 数据的示例,即在系统水平上识别肝细胞癌(HCC)的候选标志物,以及通过将差异基因表达与人类蛋白质相互作用网络的拓扑特征相结合,开发基于系统生物学的分类器,以增强 HCC 鉴别诊断的能力。

结论

LiverAtlas 是最全面的肝脏和肝脏疾病资源,它帮助生物学家和临床医生在系统水平上分析他们的数据,并将为肝脏疾病的生物标志物发现和诊断性能提升做出重要贡献。

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