Gene Set Enrichment Analysis of microRNA Functional Roles in Biological Network and System Implementation

• Main Authors: Hui-Jun Huang, 黃惠君
• Other Authors: Jung-Hsien Chiang
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/64648769163050158297

碩士 === 國立成功大學 === 資訊工程學系碩博士班 === 97 === 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.