多樣化全基因體的研究方法已經被運用到疾病分子層面的研究。即使如此，單就使用一種篩選平台的實驗技術仍相當困難去勾勒出疾病在分子機轉的輪廓。因此，「微陣列整合系統」的開發將是有助於面臨醫學研究時有更全面性的了解。然而，不同微陣列平台數據資料無法正確比較是整合時的重要問題。以基因微陣列為例，單一基因設計成數段不同序列的探針，而釐清哪一個探針所偵測的訊息才是反映基因表現的真實性即是困難問題的其中之一。我們成功地將不同微陣列平台上影像訊號重組，微陣列整合系統的建置是將多方單一高速篩選分析平台做整合，同時結合表觀基因體學、基因體學、蛋白質體學、訊息網絡與藥物學。此計畫中，我們將執行三個目標：（1）運用探針重組降低影像訊號的雜訊並建置低雜訊之微陣列整合系統，（2）建置自動化收尋生物醫學相關資料庫與彙整生物資訊資料之公共平台以結合微陣列整合系統，（3）運用生物醫學實驗技術實際驗證並評估整合後之預測結果，包括癌症轉移基因之訊息網絡、新藥療效評估與臨床病程預測。我們相信「微陣列整合系統」是可提供更好的預測結果，同時有機會提供重要之臨床觀點與疾病診斷、療效評估與治療方法選擇。 A variety of whole-genome approaches have been used to identify the molecular profiles that contribute to and reflect to diseases. Even so, it is still difficult to delineate the molecular basis of disease by only one screening technology. Integrated array system will probably have multiple implications and contribute to more comprehensive understandings when researchers face with medical issues. However, there were still several integrated problems of different array data comparisons. For example, one of the difficulties in the cross platform comparison of microarray data is to ascertain that probes on the various platforms aimed at the same gene do in fact quantify the same mRNA transcript. We succeeded to rearrange the image signals from different array platforms. Integrated array system will integrate different genome-wide screening platforms and combine epigenomics, genomics, proteomics, signaling network and pharmacology. In this proposal, the overall goals are (1) to reduce the cross hybridization noise of array signal by probe redefinition and establish integrated array system, (2) to establish an information harvesting infrastructure system, which employs softbots to collect publicly accessible datasets as well as our measurements, and (3) to identify the metastasis related candidates, the therapeutic effects of novel drug and clinical outcome predictions by using typical biomedical experiment tools. We believe that ‘integrated array system’ should provide better prediction power, and raise a possibility for the important clinical aspect in the identification of novel molecular markers for disease diagnosis, prognosis, and therapy selection. 研究期間：9908 ~ 10007
