마이크로 RNA 와 mRNA 표현형 데이터를 위한 시각적 분석

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2016. 8. 서진욱.MicroRNAs (miRNA) are short nucleotides that down-regulate its target genes. Various miRNA target prediction algorithms have used sequence complementarity between miRNA and its targets. Recently, other algorithms tried to improve sequence based miRNA target prediction by exploiting miRNA-mRNA expression profile data. Some web-based tools are also introduced to help researchers predict miRNAs targets from miRNA-mRNA expression profile dataHowever, there is still a demand for a miRNA-mRNA visual analysis tool that include quality miRNA prediction algorithms and more interactive visualizations. We presented two techniques for miRNA-mRNA interaction visualizations, Bipartite Treemap and enhanced node-link diagram. Bipartite Treemap is a new visualization technique for miRNA-mRNA interaction network that resolves occlusion problem. Enhanced node-link diagram provides interaction techniques that help users to explore miRNA-mRNA interaction network easily. We designed and implemented miRTarVis, which is an interactive visual analysis tool that predicts miRNA targets by integrating sequence based and miRNA-mRNA expression profile based miRNA target prediction algorithms, and visualizes the resulting miRNA-mRNA interaction network. miRTarVis has intuitive interface design in accordance with the analysis procedure of load, filter, predict, and visualize. It predicts miRNA targets by adopting Bayesian inference and MINE analyses, as well as conventional correlation and mutual information analyses. It visualizes a resulting miRNA-mRNA network in an interactive Bipartite Treemap as well as ehanced node-link diagram. Using miRTarVis, we analyzed miRNA-mRNA expression profile data from an experiment over asthmatic and non-asthmatic fibroblasts exposed to obese visceral exosomes. In addition, we applied miRTarVis to miRNA-mRNA expression profile data from breast cancer cell lines data to show its efficacy. miRTarVis verified its efficacy by helping its users execute miRNA target prediction easily and gain insights from miRNA-mRNA expression profile data by its interactive visualization.Chapter 1 Introduction 1 1.1 Background and Motivation 1 1.2 Main Contribution 9 1.3 Organization of the Dissertation 14 Chapter 2 miRNA target Prediction 16 2.1 MicroRNA Target Prediction Algorithms 17 2.1.1 Sequence based target prediction algorithms 22 2.1.2 MiRNA-mRNA expression profile based target prediction algorithms 29 2.2 Analysis Tools for Integrated Analysis of miRNA and mRNA 39 Chapter 3 Bipartite Treemap and Enhanced Node-Link Diagram for miRNA-mRNA Interaction Network 46 3.1 Visual representation of Bipartite Treemap 49 3.2 Node-link Diagram with Enhanced Interaction and Various Graph Layouts 54 3.3 Interfaces and Interaction Design for Bipartite Treemap and Enhanced Node-Link Diagram 58 3.4 Comparison with Other Visualization Techniques for MiRNA-mRNA Interaction Network 70 Chapter 4 miRTarVis 83 4.1 Design goals and Rationale 84 4.2 Input Data 88 4.3 MiRNA Target Prediction and Analysis Procedure 91 4.4 Visualizations in miRTarVis 98 4.5 Implementation 100 Chapter 5 Case Study 102 5.1 Analysis of miRNA-mRNA Expression Profile Data from Asthmatic and Non-asthmatic Cells by miRTarVis 102 5.2 Analysis of miRNA-mRNA Expression Profile Data using TCGA Breast Cancer Dataset 109 Chapter 6 Discussion 120 Chapter 7 Conclusion 125 Bibliography 129 요약 149Docto