Integration of bioinformatics resources for functional analysis of gene expression and proteomic data
Integration of bioinformatics resources for functional analysis of gene expression and proteomic data
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DOI：
10.2741/2449
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发表时间：
2007-09-01
影响因子：
3.1
通讯作者：
Wu, Cathy H.
中科院分区：
文献类型：
--
作者：
Huang, Hongzhan;Hu, Zhang-Zhi;Wu, Cathy H.
在后基因组时代，研究人员通过在全球范围内研究生物体，系统地研究基因功能和复杂的调控过程；然而，一个主要的挑战在于大量的、复杂的和动态的数据被维持在不同的来源，特别是来自蛋白质组学实验。需要先进的计算方法来整合、挖掘、比较分析和高通量蛋白质组学数据的功能解释。在本文的第一部分中，我们将讨论数据集成的各个方面，这些方面对于捕获与功能分析相关的所有数据非常重要。我们提供了基因组学和蛋白质组学中常用的数据库列表，并解释了连接源数据的策略，特别强调我们的ID映射服务。接下来，我们描述了iProClass，这是一个支持数据集成和蛋白质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）上目前可用的数据搜索/检索和分析工具，研究人员可以使用这些工具进行大规模的功能分析。最后，我们介绍了iProXpress (integrated Protein eXpression)，这是一个用于大规模表达数据分析的集成研究和发现平台，并展示了一个用于细胞器蛋白质组分析的原型。
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.