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整合蛋白质组学数据库和储存库的新方法。

New approaches towards integrated proteomic databases and depositories.

作者信息

Rohlff Christian

机构信息

Oxford Genome Sciences Ltd, 22 The Quadrant, Barton Lane, Abingdon Sciences Park, Abingdon, OX14 3YS, UK.

出版信息

Expert Rev Proteomics. 2004 Oct;1(3):267-74. doi: 10.1586/14789450.1.3.267.

Abstract

Since the publication of the human genome, two key points have emerged. First, it is still not certain which regions of the genome code for proteins. Second, the number of discrete protein-coding genes is far fewer than the number of different proteins. Proteomics has the potential to address some of these postgenomic issues if the obstacles that we face can be overcome in our efforts to combine proteomic and genomic data. There are many challenges associated with high-throughput and high-output proteomic technologies. Consequently, for proteomics to continue at its current growth rate, new approaches must be developed to ease data management and data mining. Initiatives have been launched to develop standard data formats for exchanging mass spectrometry proteomic data, including the Proteomics Standards Initiative formed by the Human Proteome Organization. Databases such as SwissProt and Uniprot are publicly available repositories for protein sequences annotated for function, subcellular location and known potential post-translational modifications. The availability of bioinformatics solutions is crucial for proteomics technologies to fulfil their promise of adding further definition to the functional output of the human genome. The aim of the Oxford Genome Anatomy Project is to provide a framework for integrating molecular, cellular, phenotypic and clinical information with experimental genetic and proteomics data. This perspective also discusses models to make the Oxford Genome Anatomy Project accessible and beneficial for academic and commercial research and development.

摘要

自人类基因组公布以来,出现了两个关键点。第一,基因组中哪些区域编码蛋白质仍不确定。第二,离散的蛋白质编码基因数量远少于不同蛋白质的数量。如果我们在整合蛋白质组学和基因组数据的努力中能够克服所面临的障碍,蛋白质组学有潜力解决一些后基因组问题。高通量和高产出的蛋白质组学技术存在许多挑战。因此,为使蛋白质组学以当前的增长速度持续发展,必须开发新方法来简化数据管理和数据挖掘。已经发起了一些倡议来开发用于交换质谱蛋白质组学数据的标准数据格式,包括人类蛋白质组组织组建的蛋白质组学标准倡议。诸如SwissProt和Uniprot等数据库是公开可用的蛋白质序列储存库,这些序列标注了功能、亚细胞定位和已知的潜在翻译后修饰。生物信息学解决方案的可用性对于蛋白质组学技术兑现为人类基因组的功能输出增添更多定义的承诺至关重要。牛津基因组剖析计划的目标是提供一个框架,将分子、细胞、表型和临床信息与实验性遗传和蛋白质组学数据整合起来。本文还讨论了使牛津基因组剖析计划便于学术和商业研发使用并使其受益的模式。

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