Non-coding RNAs (ncRNAs) have important biological functions such as regulation of gene expression and disease causality. These ncRNAs exert their functions by interacting with other molecules, such as messenger RNAs (mRNAs). Thus RNA-RNA interaction studies are important for understanding the gene regulation mechanism and for curing ncRNAs related diseases. This thesis contributes to RNA-RNA interaction prediction problem, construction of a comprehensive human micro RNAs (miRNAs)-related database and data mining on high throughput RNA-RNA interaction data. / On RNA-RNA interaction prediction problem, a novel energy model is proposed and a GA based algorithm is developed, namely RIPGA. The experiments results show that the novel energy model outperforms the state of the art model, which is called Turner energy model, RIPGA with novel energy model also outperforms two state of the art programs, which are called inRNAs and RactIP. / On construction of a comprehensive human miRNA-related database, data are collected and cleansed from three state of the art databases related to human miRNAs, which are called miR-TarBase, miRBase and HMDD v2.0. A network is constructed from these data to present the complete relationships of the miRNAs because the relationships are only partial covered by the existing databases. A website and database are setup for data query, visualization and analysis functions to complement the existing databases. / On data mining on high-throughput RNA-RNA interaction data, four characteristics of RNA-RNA interaction are identified from the high-throughput data. We believe these characteristics are potential explanations of the high degree of connectivity of some miRNAs. These characteristics are also important scientific knowledge for future research on RNA-RNA interaction and control for biomedical applications. / 非編碼核糖核酸(ncRNAs)有重要的生物功能，例如：基因表現的調控和疾病的因果關係。這些ncRNAs透過與其他分子的互相作用來發揮作用，例如：信使核糖核酸(mRNAs)。因此，核糖核酸互相作用的研究對理解基因表現的調控和治愈與ncRNAs有關的疾病十分重要。本論文集中解決核糖核酸互相作用的預測問題、建設人類微核糖核酸(miRNAs)綜合數據庫和高通量核糖核酸互相作用數據的數據挖掘。 / 針對核糖核酸互相作用的預測問題，我們提出了一個新的能量模型和開發了一個基於遺傳算法的算法，即RIPGA。實驗數據顯示新的能量模型比最先進的模型﹐即特納能量模型做得更好。而RIPGA亦比最先進的inRNAs和RacIP做得更好。 / 針對建設人類微核糖核酸綜合數據庫，我們收集及潔淨來自三個最先進的數據庫的數據，即miRTarBase，miRBase和HMDDv2.0。我們由這些數據建設了一個網絡來表達完整的miRNAs關係，因為現存的數據庫只覆蓋了部份的關係。我們亦設置了網站和數據庫，並提供數據查詢、可視化及分析的功能，以補足現存的數據庫。 / 針對高通量核糖核酸互相作用數據的數據挖掘，我們從高通量核糖核酸互相作用數據中認出四個核糖核酸互相作用的特點。我們相信這些特點是部份高連通miRNAs的可能的解釋。這些特點對核糖核酸互相作用及控制的未來研究和生物醫學應用亦是重要的科學知識。 / Cheung, Kwan Yau. / Thesis M.Phil. Chinese University of Hong Kong 2015. / Includes bibliographical references (leaves 149-154). / Abstracts also in Chinese. / Title from PDF title page (viewed on 05, October, 2016). / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only.