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人类蛋白质参考数据库的开发作为研究人类系统生物学的初始平台。

Development of human protein reference database as an initial platform for approaching systems biology in humans.

作者信息

Peri Suraj, Navarro J Daniel, Amanchy Ramars, Kristiansen Troels Z, Jonnalagadda Chandra Kiran, Surendranath Vineeth, Niranjan Vidya, Muthusamy Babylakshmi, Gandhi T K B, Gronborg Mads, Ibarrola Nieves, Deshpande Nandan, Shanker K, Shivashankar H N, Rashmi B P, Ramya M A, Zhao Zhixing, Chandrika K N, Padma N, Harsha H C, Yatish A J, Kavitha M P, Menezes Minal, Choudhury Dipanwita Roy, Suresh Shubha, Ghosh Neelanjana, Saravana R, Chandran Sreenath, Krishna Subhalakshmi, Joy Mary, Anand Sanjeev K, Madavan V, Joseph Ansamma, Wong Guang W, Schiemann William P, Constantinescu Stefan N, Huang Lily, Khosravi-Far Roya, Steen Hanno, Tewari Muneesh, Ghaffari Saghi, Blobe Gerard C, Dang Chi V, Garcia Joe G N, Pevsner Jonathan, Jensen Ole N, Roepstorff Peter, Deshpande Krishna S, Chinnaiyan Arul M, Hamosh Ada, Chakravarti Aravinda, Pandey Akhilesh

机构信息

McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland 21287, USA.

出版信息

Genome Res. 2003 Oct;13(10):2363-71. doi: 10.1101/gr.1680803.

Abstract

Human Protein Reference Database (HPRD) is an object database that integrates a wealth of information relevant to the function of human proteins in health and disease. Data pertaining to thousands of protein-protein interactions, posttranslational modifications, enzyme/substrate relationships, disease associations, tissue expression, and subcellular localization were extracted from the literature for a nonredundant set of 2750 human proteins. Almost all the information was obtained manually by biologists who read and interpreted >300,000 published articles during the annotation process. This database, which has an intuitive query interface allowing easy access to all the features of proteins, was built by using open source technologies and will be freely available at http://www.hprd.org to the academic community. This unified bioinformatics platform will be useful in cataloging and mining the large number of proteomic interactions and alterations that will be discovered in the postgenomic era.

摘要

人类蛋白质参考数据库(HPRD)是一个对象数据库,它整合了大量与人类蛋白质在健康和疾病中的功能相关的信息。从文献中提取了与数千种蛋白质-蛋白质相互作用、翻译后修饰、酶/底物关系、疾病关联、组织表达和亚细胞定位有关的数据,涉及2750种非冗余人类蛋白质。几乎所有信息都是由生物学家在注释过程中通过阅读和解读超过30万篇已发表文章手动获取的。该数据库具有直观的查询界面,便于访问蛋白质的所有特征,它是使用开源技术构建的,并将在http://www.hprd.org上免费提供给学术界。这个统一的生物信息学平台将有助于编目和挖掘在后基因组时代发现的大量蛋白质组相互作用和变化。

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7
Overview of the Alliance for Cellular Signaling.细胞信号传导联盟概述。
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Computational systems biology.计算系统生物学
Nature. 2002 Nov 14;420(6912):206-10. doi: 10.1038/nature01254.
10
Databases and tools for browsing genomes.用于浏览基因组的数据库和工具。
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