Functional annotation and network reconstruction through cross-platform integration of microarray data
Functional annotation and network reconstruction through cross-platform integration of microarray data
复制标题
DOI：
10.1038/nbt1058
复制
发表时间：
2005-02-01
影响因子：
46.9
通讯作者：
Wong, WH
中科院分区：
文献类型：
--
作者：
Zhou, XHJ;Kao, MCJ;Wong, WH
微阵列数据的快速积累意味着需要一些方法来有效整合由不同平台产生的数据。在此我们介绍一种方法，二阶表达分析，它通过首先从每个数据集提取表达模式作为元信息（一阶表达分析），然后跨多个数据集对其进行分析，从而解决这一难题。我们以酵母作为模型系统，展示了我们这种方法的两个显著优势：我们能够识别具有相同功能但没有共表达模式的基因，并且我们能够通过克服一个关键障碍，即转录因子活性的量化，阐明转录因子之间在调控网络重建中的协同作用。文献中报道的以及我们实验室所进行的实验都支持了我们的大量预测。
The rapid accumulation of microarray data translates into a need for methods to effectively integrate data generated with different platforms. Here we introduce an approach, 2(nd)-order expression analysis, that addresses this challenge by first extracting expression patterns as meta-information from each data set (1(st)-order expression analysis) and then analyzing them across multiple data sets. Using yeast as a model system, we demonstrate two distinct advantages of our approach: we can identify genes of the same function yet without coexpression patterns and we can elucidate the cooperativities between transcription factors for regulatory network reconstruction by overcoming a key obstacle, namely the quantification of activities of transcription factors. Experiments reported in the literature and performed in our lab support a significant number of our predictions.