生命最終都是仰賴太陽的能量，而光合作用是唯一可以捕捉這些能量的重要生物過程，且光合作用也是綠色能源的主要技術。而光合作用的光適應行為對於植物而言是一個最佳化光合作用效率的重要生物機制。不過，到目前為止，植物是如何調控光合作用光適應行為來平衡外界光線對它產生的刺激，在分子層面上的機制都還是不為人知。這篇文章中，我們提出一個系統化的方法，結合時間序列的阿拉伯芥微陣列基因片(microarray)實驗數據來建構基因調控網路並且探討隱藏在光合作用光適應行為背後的生物機制。
我們整理文獻記載的資訊與利用預測的資料庫來建構一個粗略的基因調控網路(rough gene regulatory network)，接著，引入動態基因調控模型模擬轉錄因子與基因之間的調控關係，接著利用時間序列的microarray data結合maximum likelihood系統參數估測與Akaike Information Criteria (AIC)系統複雜度的偵查方法，將一些存在於粗略的基因調控網路中不具生物重要性的轉錄調控作用刪掉，經由不斷重複的篩選，最後得到一個精確的基因調控網路(refined gene regulatory network)，這個精確的基因調控網路是接近植物在光適應行為下真實存在於細胞核中轉錄因子與基因之間的調控關係。我們比較不同光照下的兩個基因網路，我們辨識出在不同光照下重要的轉錄因子(transcription factor)，將它視為基因調控網路的中樞，進一步利用基因網路結構的觀點來探討網路系統的強健性。這些結果讓我們對光合作用光適應機制更加了解，希望我們的結果可以讓更多人對這個研究主題更感興趣。

Photosynthetic light acclimation is an important process in plant for the optimal efficiency of photosynthesis, and photosynthesis is the core technology of green energy. However, at present, little is known about molecular mechanisms how to regulate photosynthetic light acclimation response. In this study, a systematic method is proposed to investigate this mechanism through constructing gene regulatory networks from microarray data of Arabidopsis thaliana.
A rough gene regulatory network of photosynthetic light acclimation is constructed from the data mining of literature and prediction database. Then the rough gene regulatory network is pruned by microarray data of Arabidopsis thaliana via maximum likelihood system identification and Akaike’s system order detection to obtain a refined gene regulatory network close to the real gene regulatory network of photosynthetic light acclimation. By comparing the gene regulatory networks under PSI-PSII light shift and PSII-PSI light shift, we can identify important transcription factors at different light conditions. Further, the robustness of gene network is also discussed under different light conditions from hub and weak linkage point of view to provide more insight into the mechanism of photosynthesis.

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