Self-cleaving ribozymes are the smallest catalytic RNAs found in nature, and are believed to have played an important role in the origin of life. The evidence that these natural RNAs can catalyze site-specific scission of their phosphodiester backbone demonstrates that RNAs can also fold into intricate functionally specific structures. Despite the biological importance of ribozymes, their structural characterization remains challenging because of the difficulty to crystallize. Moreover, their sizes are often too large for NMR structure determination. This thesis seeks to infer the base-pairing information of self-cleaving ribozymes by deep mutational scanning. Chapter 1 of this thesis gives an overview of self-cleaving ribozymes and current RNA structural biology techniques. In Chapters 2, 3 and 4, we performed a large-scale mutational analysis to gain structural information which is important for understanding the function of ribozymes. Generally, we constructed the mutant library of three ribozymes (CPEB3, LINE-1, OR4K15 ribozyme) from the human genome by error-prone PCR or using doped synthesis. These variants of ribozymes were assayed for their self-cleaving activity by exploiting deep sequencing for every randomized variant. A complete activity profile of each variant was acquired based on this large-scale mutational analysis. To better predict the structural information, we developed a method called covariation-induced deviation of activity (CODA). When in combination with Monte Carlo simulated annealing, it provides an accurate inference of noncanonical and all canonical Watson-Crick base pairs at 100% precision for two self-cleaving ribozymes studied (CPEB3 and twister ribozyme). By extending this method to two unknown ribozymes (LINE-1, OR4K15 ribozyme), we were able to identify the core elements and their secondary structure. According to the secondary structure information, we identified homologs of these ribozymes by using a secondary structure-based similarity search. In summary, our results show that combining deep mutational scanning and CODA analysis provides a highly accurate secondary-structure characterization of RNAs for the discovery of additional homologous sequences.