This work investigates pathways of conformational transitions in ubiquitous RNA structural motifs. In our lab, we have developed multi-scale structural datamining techniques for identification of three-dimensional structural patterns in high-resolution crystal structures of globular RNA. I have applied these techniques to identify variations in the conformations of RNA double-helices and tetraloops. The datamined structural information is used to propose reaction coordinates for conformational transitions involved in double-strand helix propagation and tetraloop folding in RNA. I have also presented an algorithm to identify stacked RNA bases. In this work, experimentally derived thermodynamic evaluation of the conformations has been used to as an additional parameter to add detail to RNA structural transitions. RNA conformational transitions help control processes in small systems such as riboswitches and in large systems such as ribosomes. Adopting functional conformations by globular RNA during a folding process also involves structural transitions. RNA double-helices and tetraloops are common, ubiquitous structural motifs in globular RNA that independently fold in to a thermodynamically stable conformation. Folding models for these motifs are proposed in this work with probable intermediates ordered along the reaction coordinates. We hypothesize that frequently observed structural states in crystals structures are analogous in conformation to stable thermodynamic â on-pathwayâ folded states. Conversely, we hypothesize that conformations that are rarely observed are improbable folding intermediates, i.e., these conformational states are â off-pathwayâ states. In general on-pathway states are assumed to be thermodynamically more stable than off-pathway states, with the exception of kinetic traps. Structural datamining shows that double helices in RNA may propagate by the â stack-ratchetâ mechanism proposed here instead of the commonly accepted zipper mechanism. Mechanistic models for RNA tetraloop folding have been proposed and validated with experimentally derived thermodynamic data. The extent of stacking between bases in RNA is variable, indicating that stacking may not be a two-state phenomenon. A novel algorithm to define and identify stacked bases at atomic resolution has also been presented in this work.