Hanczar Blaise, Henegar Corneliu, Zucker Jean-Daniel
LIPADE, University Paris Descartes, 45 rue des Saint-Peres, 75006 Paris, France.
Int J Bioinform Res Appl. 2010;6(6):628-42. doi: 10.1504/IJBRA.2010.038743.
Microarray experiments can be used for simultaneous expression of thousands of genes in various conditions. Data from these experiments are used to identify the gene involved in a particular biological phenomenon. Most current methods for such analysis assume that genes are independent. We explored the interaction between genes to identify informative gene pairs. This was based on measuring the interaction information using the information theory. We show that there are two kinds of gene interaction, redundancy and synergy. We analysed these interactions to construct a network of redundancy and conducted a functional analysis of synergic components on two public datasets.
微阵列实验可用于在各种条件下同时表达数千个基因。这些实验的数据用于识别参与特定生物学现象的基因。目前大多数此类分析方法都假定基因是独立的。我们探索了基因之间的相互作用以识别信息丰富的基因对。这是基于使用信息论来测量相互作用信息。我们表明存在两种基因相互作用，即冗余和协同。我们分析了这些相互作用以构建冗余网络，并在两个公共数据集上对协同组件进行了功能分析。
