在後基因體時代中，微陣列晶片實驗(microarray)是目前最常被生物學家用來進行觀察基因表現與功能研究，能幫助更了解生物體內所發生的化學反應。其優點為快速與高產能，能夠同時全面性檢測大量基因。但是後續從微陣列晶片實驗判讀出有生物意義的結論是不易的。Gene Set Enrichment Analysis(GSEA)為2005年Subramanian提出的微陣列晶片實驗資料分析方法，由基因表現值與不同生物概念所形成的基因集(gene set)進行統計分析，檢定出基因集在微陣列晶片實驗上是否具有顯著性。在本研究中，我們建置一套GSEA管線化分析系統，其結果輸出之後能夠建構出交互作用網路。進一步從這樣的網路中，找出多個概念共同交集的網路區塊做文獻註解(annotation)，並且加以視覺化呈現。微型核糖核酸(microRNA)是近年來才發現的，研究顯示微型核糖核酸對於生物路徑(pathway)上基因的調控，扮演著重要的角色，本論文以微型核糖核酸和生物路徑兩種生物概念的基因集為主，來提供疾病與基因的關聯性。
實驗結果顯示從Gene Expression Omnibus (GEO)提供的微陣列晶片實驗 GSE4479中，得到在腦瘤病患裡，miR-155、miR-125b分別調控SMAD2、ERBB3基因表現量，使之基因表現量降低，且SMAD2所屬的生物路徑，在腦瘤裡呈現著異常反應，這樣在疾病裡連鎖的調控資訊，是從微型核糖核酸為根基組織成的網路中擷取出來。我們期能從中辨識出影響疾病發展的關鍵，並提供給生物學者解讀更多面向的生物意義。

In recent years, DNA microarrays have been widely not only applied on gene functional role analysis but also supported on interaction information across different species. Furthermore, it has the advantage of quickly obtaining gene profiles through whole genome. However, how to evaluate gene expression level is still a tough problem. To overcome this problem, Gene Set Enrichment Analysis (GSEA) was proposed in 2005 for better interpreting microarray expression data. GSEA focus on gene sets, groups of genes that share common biological concepts. Based on GSEA, our study is to develop a powerful system aiming at standardizing, analyzing and generating results including biological interaction networks and experiment-associated pathway maps. Moreover, we provide important regulating sub-networks across biological concepts with literature annotation and visualizing those networks. miRNA has been discovered recently as a stable regulator and several researches reveal that miRNA plays an important role in regulated genes involved pathway. Our system provides relationships between miRNA and pathway under disease condition.
We retrieve microarray data (GSE4479) from Gene Expression Omnibus (GEO) and analyze the data through our pipeline. The results show that miR-155 suppresses the expression level of SMAD2 and miR-125b inhibits the expression level of ERBB3 in glioma. Besides, the expression of glioma pathway is significantly enriched. We hope the tool can support for mining more information and the results can be provided for implications to miRNA research.

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