藉由有時間序列的生物晶片(microarray)實驗，可以獲得大量有關於基因間調控關係的訊息。而由這些訊息可以建立出基因之間的動態模型，這些模型將顯示出基因跟基因之間的調控關係。而由於直接的去探討基因間的調控關係將會造成一連串複雜且難以看出其中調控的關鍵，所以這裡吾人藉由群組(cluster)以降低其複雜度，且由於群組起來的基因之間本身將具有一定的相關程度，這將可獲得更多有關於基因之間的關係，因吾人希望能從生物晶片中能盡量獲取其中基因間重要關係，所以又加入動態模型以尋求其中基因之間的調控關係。而這裡吾人選用目前較多文獻記載的酵母菌檢視這方法在高溫下的動態調控網路的效果。
而其結果，吾人確能找到相關的基因調控關係之文獻記載，此方法確有一定能力以尋找出生物中的一些調控關係。藉由此方法亦可尋找出一些未知的關係將有利於未來研究時的實驗的依據。

How to construct gene regulatory networks from microarray data has attracted research attention in recent years. Time-series profiles of gene expression generated by DNA microarrays possess rich information to construct dynamic models of transcription behaviors. In this study, with the help of correlation clustering, the AutoRegressive with eXogenous input (ARX) models is introduced to construct a gene regulatory network in response to heat shock in the environment and may provide new insights into the thermo-tolerance mechanism of biological processes under heat shock stress. If all microarray data and the related genes are included, the gene regulatory network would become too complex to get their important regulatory relationships. So a cluster regulatory network is constructed at first to simplify the construction procedure of the complex gene regulatory network of heat shock. Therefore, the fuzzy K-means algorithm is used to cluster the genes with similar expression profiles under heat shock stress. Then a cluster gene regulatory network for heat shock is constructed based on the ARX model and the averaging method. The sparseness of the cluster gene regulatory network is also considered using Akaike’s Information criterion. Finally, we construct the gene regulatory network of heat shock based on the interactive information of the constructed cluster regulatory networks to find some possible gene regulatory mechanisms under heat shock stress.

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