在免疫發炎反應中，NF-κB是一個非常重要的轉錄因子，除了發炎外，細胞的增生和死亡，或是癌細胞的生長也都和NF-κB有非常密切的關係，然而NF-κB是由兩個轉錄因子結合產生的複合體，以目前生物實驗的技術難以直接量測細胞中NF-κB的濃度多寡。

目前在NF-κB相關的研究中，有利用各反應動力學模式和定量化參數，以正向工程方式建構的IKK至NF-κB信號傳遞模型；預測IKK剌激誘發之NF-κB活性。NF-κB 的活性會轉錄為基因表現，目前文獻己發展出一些以雙成份網絡分解(bipartite network decomposition)數學工具，如NCA方法，加上一些生物調控網路的資訊；將微陣列晶片(microarray)數據，還原為調控網路模型及轉錄因子活性。

本研究嘗試將正向信號傳遞預測和逆向調控網路重建的結果連結在一起，驗證在毒素刺激下轉錄因子NF-κB活性的動態變化。根據兩組毒素刺激方式不同的microarry data，用NCA方法重建出NF-κB活性，並用IKK至NF-κB信號傳遞模型模擬產生NF-κB反應的IKK活性，將模擬結果與原來的microarry實驗刺激大小進行驗證，我們發現刺毒素刺激度較小的體內刺激中，IKK活性也小，對應的NF-κB活性在刺激過後的1到2小時達到波鋒，之後活性急速下降，刺激9小時後活性緩後下降直到原來的平衡值；而毒素刺激度較大的體外刺激，所產生的IKK活性也大，在主要刺激過後的仍有少量IKK殘餘，所產生的NF-κB活性同樣在1到2小時活性最大，之後活性快速下降，在一段時間後，由於IKK殘餘使得NF-κB活性再次上升並維持在一個較大平衡值。
我們嘗試將此研究方法應用於腫瘤細胞上，利用T84細胞的microarray與生物調控網路資訊建立與發炎相關調控網路類似的網路結構，然而此組microarray雜訊過大，不利於分析，但是我們發現T84細胞的基因表現中，IL8表現明顯高於結構中的其他基因表現，接著我們根據T84細胞原始microarry實驗刺激情況，利用訊號傳遞模型推測IKK和NF-κB活性情形，雖然研究方法還無法完全應用於癌症方面，但希望將來能將同樣方法應用於和發炎反應有關的腫瘤細胞生長，以期能完全了解發炎反應和腫瘤生長的關係。

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