基因的表現必須依賴轉錄因子(Transcription factor)辨識所對應的調控motif。然而基因表現如何藉由轉錄因子辨識順式因子(cis-element)之間的交互作用所調控，到目前為止對其瞭解仍是相當有限。本篇論文中，吾人定義一種cis調控網路的系統，它主要由順式因子及辨識它的轉錄因子所構成，並發展出一種動態模型來研究這種網路的動態特性與功能性結構。論文中，吾人主要研究酵母菌細胞分裂週期(cell cycle)基因的cis 調控網路，研究中吾人提出一種新的交叉基因辨識技巧，此技巧是針對感興趣的目標基因，利用生物晶片實驗資料與調控motif 的資訊，找出一群與該目標基因具有相同motif的基因，進而幫助分析多轉錄因子如何調控酵母菌細胞分裂週期基因的表現，並找出隱藏在cis 調控網路中轉錄因子之間交互作用所產生的調控能力。藉由這樣的動態模型分析，吾人不但可以對於每個轉錄及順式因子辨別量化出個別及交互作用所產生的調控能力特性，並可藉由這些辨別出的調控特性，發展出一種新的預測基因表現的方法。藉由這樣的預測方法，亦能有效的預測出基因的表現結果。本論文的分析技巧未來將可以應用在分析更複雜的真核生物，並探討基因調控序列間的演化變異。

Gene expression programs depend on recognition of regulatory motifs by transcription factors (TFs), but how TFs regulate gene expression via recognition of cis elements is still not very clear. To study this issue, we define the cis-regulatory circuit of a gene as a system that consists of the cis elements and the interactions among their recognizing TFs and we develop a dynamic model for studying the functional architecture and dynamics of the circuit. In current approaches, a cis-regulatory circuit is constructed by a mutagenesis or motif-deletion scheme, which changes the structure of the circuit and therefore cannot give intact information for constructing the circuit. In our approach, however, one difficulty is that in each circuit, there are multiple regulatory inputs, but there is only one expression output, which is not sufficient for estimating the many parameters in our model of the circuit. We overcome this difficulty by noting that within a cluster of genes with similar functions the cis elements and the interactions of their TFs overlap among genes, so that sufficient information for constructing the cis-regulatory circuit of a gene can be obtained by simultaneously employing the expression profiles of the genes in the cluster.
A novel cross-gene identification scheme is proposed to reveal how multiple TFs coordinate to regulate gene transcription in the yeast cell cycle and to uncover hidden regulatory functions of cis-regulatory circuits. The scheme constructs the cis-regulatory circuit of each gene in a cluster of genes with overlapping binding motifs. It uses microarray data and data from genome-wide analysis of TF binding locations by chromatin immunoprecipitation. Dynamic models of the cis-regulatory circuits of the genes under study are developed according to their binding motifs and all possible interactions among their TFs. The rate parameters and regulation functions of the cis-regulatory circuits are estimated from microarray data. One advantage of this approach over that based on a mutagenesis or deletion scheme is that it is based on data obtained from the intact cis-regulatory circuits. Another advantage is that a dynamic model can quantitatively characterize the regulatory function of each of the TFs that recognize the cis elements of the gene and the interactions (cooperativities) among the TFs. Our model discerns not only the activation or repression of cis-regulatory elements by TFs but also the ability of the TFs to regulate the gene expression from a systems biology point of view. This approach may be also useful for constructing cis-regulatory circuits in more complex eukaryotes than yeast. After the cis-regulatory circuits of interest are described by explicit dynamic equations, some applications will be straightforward by the analysis and comparison of explicit values in the dynamic model. For example, the evolution of cis-regulatory circuits may be studied by comparing the values of dynamic parameters of different yeast strains.

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