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生命科学中的生物信息学策略:从数据处理与数据仓储到生物知识提取。

Bioinformatics strategies in life sciences: from data processing and data warehousing to biological knowledge extraction.

作者信息

Thiele Herbert, Glandorf Jörg, Hufnagel Peter

机构信息

Bruker Daltonik GmbH, Fahrenheitstr. 4, Bremen, Germany.

出版信息

J Integr Bioinform. 2010 May 27;7(1):141. doi: 10.2390/biecoll-jib-2010-141.

DOI:10.2390/biecoll-jib-2010-141
PMID:20508300
Abstract

With the large variety of Proteomics workflows, as well as the large variety of instruments and data-analysis software available, researchers today face major challenges validating and comparing their Proteomics data. Here we present a new generation of the ProteinScape bioinformatics platform, now enabling researchers to manage Proteomics data from the generation and data warehousing to a central data repository with a strong focus on the improved accuracy, reproducibility and comparability demanded by many researchers in the field. It addresses scientists; current needs in proteomics identification, quantification and validation. But producing large protein lists is not the end point in Proteomics, where one ultimately aims to answer specific questions about the biological condition or disease model of the analyzed sample. In this context, a new tool has been developed at the Spanish Centro Nacional de Biotecnologia Proteomics Facility termed PIKE (Protein information and Knowledge Extractor) that allows researchers to control, filter and access specific information from genomics and proteomic databases, to understand the role and relationships of the proteins identified in the experiments. Additionally, an EU funded project, ProDac, has coordinated systematic data collection in public standards-compliant repositories like PRIDE. This will cover all aspects from generating MS data in the laboratory, assembling the whole annotation information and storing it together with identifications in a standardised format.

摘要

由于蛋白质组学工作流程种类繁多,以及现有仪器和数据分析软件种类繁多,如今研究人员在验证和比较蛋白质组学数据上面临重大挑战。在此,我们展示新一代的ProteinScape生物信息学平台,现在它能使研究人员管理蛋白质组学数据,从数据生成、数据存储到中央数据存储库,特别关注该领域许多研究人员所要求的提高准确性、可重复性和可比性。它满足了科学家在蛋白质组学鉴定、定量和验证方面的当前需求。但是生成大量蛋白质列表并非蛋白质组学的终点,蛋白质组学最终旨在回答有关被分析样品的生物学状况或疾病模型的特定问题。在此背景下,西班牙国家生物技术中心蛋白质组学设施开发了一种名为PIKE(蛋白质信息和知识提取器)的新工具,它使研究人员能够控制、筛选并从基因组学和蛋白质组学数据库中获取特定信息,以了解实验中鉴定出的蛋白质的作用和关系。此外,一个由欧盟资助的项目ProDac,已协调在诸如PRIDE等符合公共标准的存储库中进行系统的数据收集。这将涵盖从在实验室生成质谱数据、汇编完整注释信息并将其与鉴定结果一起以标准化格式存储的所有方面。

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Bioinformatics strategies in life sciences: from data processing and data warehousing to biological knowledge extraction.生命科学中的生物信息学策略:从数据处理与数据仓储到生物知识提取。
J Integr Bioinform. 2010 May 27;7(1):141. doi: 10.2390/biecoll-jib-2010-141.
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