在特定組織基因找尋具有鑑別性之調控因子組合

Prediction of Tissue-Specific Regulatory Sites Based on Differential Analysis of Gene Expression in Human Tissues

張惠玲(Huei-Lin chang)

指導教授 ： 劉寶鈞 ； 洪炯宗

元智大學/資訊學院/資訊工程學系/碩士(2002年)

摘要

現今有很多大規模的基因表現分析的資料庫，例如：UniGene和dbEST。我們利用基因表現資料庫所提供的資訊以分析器官專一基因(Tissue-specific Genes)。這些器官專一基因很可能是被一群轉錄基因所調控。實驗中，我利用統計的方法以分析基因表現的資料庫以找出器官專一基因，將基因分群到各器官中 (Uterus, Ovary, Brain, Liver, Skeletal Muscle, Retina )。TRANSFAC則提供已知的轉錄因子，RSDB提供重復序列。將本文標記轉錄因子及重復序列定位於基因前的促進區域。應用資料探勘(Data Mining)技術於重復序列及轉錄因子的組合。再從關聯性規則中，利用統計方法出較有意義的，並去除多餘的規則，再從規則裡的重復序列中找尋可能的轉錄因子。由於不用轉錄因子組合的黏合會造成基因的轉錄的不同，因此我們進而利用統計方法找出不用器官上之器官專一基因的轉錄因子。我們在轉錄因子上得到豐沛有價值的資訊並將結果公開在http:140.115.155.78/~piyo/bodysystem/。

關鍵字

調控因子 ； 基因表現 ； 人類器官 ； 資料探勘

並列摘要

This study attempts to mine putative binding site on how combinations of the known regulatory sites and over-represented repetitive elements are distributed in the promoter regions of considered groups of differentially expressed genes. We also perform a computational and statistical study on a large set of gene expression data consist of six adult human tissues, i.e. Uterus, Ovary, Brain, Liver, Skeletal muscle, and Retina. We propose a data mining approach to statistically discover the significant and tissue-specific combinations of known regulatory sites and over-represented repetitive sequences, which are distributed in the promoter regions of groups of genes with higher expression in the same tissue than other tissues. The association rules mined would facilitate to predict putative regulatory elements and identify genes potentially co-regulated by the putative regulatory elements. The over-represented repetitive sequences appearing in the associations found are possible to be putative TF binding sites or the other regulatory signals correlated to occurrences of known TF binding sites.

並列關鍵字

Regulatory Sites ； Gene Expression ； Human Tissue ； data mining

參考文獻

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