基因微陣列反轉量分析基因的單一抑制調控

Analysis of Negative Regulation by Single Gene Using Inverted Gene Expression Data

基因微陣列技術的使用，有助於基因表現的定量分析，以了解基因的功能。我們用組織特徵圖類神經網路分析酵母菌從無氧轉變到有氧生活代謝轉變的微陣列基因表現資料，以探索呈現負調控的基因對。藉由廣為大家所熟悉的叢集分析概念，再加上時間序列資料反轉的構想，便能將隨時間序列發展趨勢相反的酵母菌基因，成功的聚集在同一叢集中。最後配對出45組時間序列資料趨勢發展最完全相反的酵母菌基因組合。本次研究所提出的方法使得原本難以分析的基因抑制關係，得以藉由簡單而被廣泛使用的叢集分析方法來探討。

The data produced from DNA microarray are very suitable for massively parallel comparative analysis of gene behavior. Especially, by analyzing gene expression data from DNA microarrays, many types of knowledge may be discovered, including gene regulation network, genes involved in cell cycle, as well as relations between genes and genetic diseases. In this paper, we propose a novel method, which we call inverted clustering, for identifying gene pairs with negative regulation relationship by using temporal gene expression data. An integral part of our method is the use of data inversion to assess if the temporal expression profiles of two genes are opposite. If a gene is negatively regulated by another single gene, this pair of genes is very likely to have opposite temporal gene expression profiles. Self-organizing feature map (SOM) is an extensively used technique for cluster analysis. As a result of integrating SOM and the proposed data inversion method in analyzing temporal expression data of yeast genes during a diauxic shift, we identify 45 pairs of yeast genes with most opposite temporal expression profiles. Although the proposed data inversion method is very simple, it would make the extensively used cluster analysis technique an effective approach for the identification of gene pairs with negative regulation relationship.