Prediction of viral microRNA precursor base on RNA folding topology and structural features

• Main Authors: Yu-Chuan Teng, 鄧祐銓
• Other Authors: Tzong-Yi Lee
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/s66zd7

碩士 === 元智大學 === 資訊工程學系 === 101 === MicroRNA (miRNA) is a group of non-coding RNAs (~21-25 nucleotides), which participates in post-transcriptional regulation of gene expression. MiRNA play an important role of biological processes including cell developmental timing, cell proliferation, differentiation, dying or even tissue, organ formation, embryonic development and control of disease or cancer. By way of miRNA regulation mechanism is to be used in the pathological, it can be more effectively prevention and treatment. In addition to through biological experiments to find microRNA, calculate statistical oriented methods and machine learning techniques are often to predict the precursor microRNA which contain the mature microRNA. It presents a good performance and able to reduce the cost of biological experiments. This study is to use the way of computes to predict the viral microRNA precursor. We use the viruses’ pre-miRNA data from the latest released of miRBase to be the positive dataset. Collect and Generate different sequence or fragment including viral sequence / human pre-miRNA / Pseudo-8494 for negative dataset. In order to establish the training model for viral microRNA precursor, we converted the sequence / fragment to RNA secondary structure and using variety of different structural features. In the simulation and prediction results, it also achieves the accuracy higher than 83% and better than most of the related web tools.