Ariadne Genomics, Inc., Rockville, Maryland, United States of America.
PLoS One. 2010 Feb 17;5(2):e9256. doi: 10.1371/journal.pone.0009256.
Microarray-based expression profiling of living systems is a quick and inexpensive method to obtain insights into the nature of various diseases and phenotypes. A typical microarray profile can yield hundreds or even thousands of differentially expressed genes and finding biologically plausible themes or regulatory mechanisms underlying these changes is a non-trivial and daunting task. We describe a novel approach for systems-level interpretation of microarray expression data using a manually constructed "overview" pathway depicting the main cellular signaling channels (Atlas of Signaling). Currently, the developed pathway focuses on signal transduction from surface receptors to transcription factors and further transcriptional regulation of cellular "workhorse" proteins. We show how the constructed Atlas of Signaling in combination with an enrichment analysis algorithm allows quick identification and visualization of the main signaling cascades and cellular processes affected in a gene expression profiling experiment. We validate our approach using several publicly available gene expression datasets.
基于微阵列的生物系统表达谱分析是一种快速、廉价的方法，可以深入了解各种疾病和表型的本质。一个典型的微阵列图谱可以产生数百甚至数千个差异表达的基因，而发现这些变化背后的生物学上合理的主题或调节机制是一项非平凡且艰巨的任务。我们描述了一种使用人工构建的“概述”途径对微阵列表达数据进行系统水平解释的新方法，该途径描绘了主要的细胞信号通道（信号转导图谱）。目前，开发的途径主要集中在从表面受体到转录因子的信号转导，以及对细胞“主力军”蛋白的转录调控。我们展示了如何构建的信号转导图谱与富集分析算法相结合，可以快速识别和可视化基因表达谱实验中受影响的主要信号级联和细胞过程。我们使用几个公开可用的基因表达数据集验证了我们的方法。
