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整合生物信息学资源用于基因表达和蛋白质组学数据的功能分析。

Integration of bioinformatics resources for functional analysis of gene expression and proteomic data.

作者信息

Huang Hongzhan, Hu Zhang-Zhi, Arighi Cecilia N, Wu Cathy H

机构信息

Protein Information Resource (PIR), Department of Biochemistry and Molecular and Cellular Biology, Georgetown University Medical Center, Washington, DC 20007, USA.

出版信息

Front Biosci. 2007 Sep 1;12:5071-88. doi: 10.2741/2449.

Abstract

In the post-genome era, researchers are systematically tackling gene functions and complex regulatory processes by studying organisms on a global scale; however, a major challenge lies in the voluminous, complex, and dynamic data being maintained in heterogeneous sources, especially from proteomics experiments. Advanced computational methods are needed for integration, mining, comparative analysis, and functional interpretation of high-throughput proteomic data. In the first part of this review, we discuss aspects of data integration important for capturing all data relevant to functional analysis. We provide a list of databases commonly used in genomics and proteomics and explain strategies to connect the source data, with especial emphasis on our ID mapping service. Next, we describe iProClass, a central data infrastructure that supports both data integration and functional annotation of proteins, and give a brief introduction to the data search/retrieval and analysis tools currently available at our website (http://pir.georgetown.edu) that researchers can use for large-scale functional analysis. In the last part, we introduce iProXpress (integrated Protein eXpression), an integrated research and discovery platform for large-scale expression data analysis, and we show a prototype that has been useful for organelle proteome analysis.

摘要

在后基因组时代,研究人员通过在全球范围内研究生物体来系统地攻克基因功能和复杂的调控过程;然而,一个主要挑战在于异构数据源中所维护的海量、复杂且动态的数据,尤其是来自蛋白质组学实验的数据。需要先进的计算方法来对高通量蛋白质组学数据进行整合、挖掘、比较分析和功能解读。在本综述的第一部分,我们讨论数据整合的各个方面,这些方面对于获取与功能分析相关的所有数据至关重要。我们提供了基因组学和蛋白质组学中常用数据库的列表,并解释了连接源数据的策略,特别强调了我们的ID映射服务。接下来,我们描述了iProClass,这是一个支持蛋白质数据整合和功能注释的中央数据基础设施,并简要介绍了我们网站(http://pir.georgetown.edu)目前提供的数据搜索/检索和分析工具,研究人员可将其用于大规模功能分析。在最后一部分,我们介绍了iProXpress(整合蛋白质表达),这是一个用于大规模表达数据分析的综合研究与发现平台,并展示了一个对细胞器蛋白质组分析有用的原型。

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