A heuristic approach to RNA secondary structure prediction based on an object-oriented representation

This research applies object-oriented methods to fundamental problems in genetics research. It has resulted in the development and implementation of the HAFA algorithm for RNA secondary structure prediction and alignment. HAFA is significantly faster than traditional techniques and is particularly useful in identifying evolutionary changes in RNA molecules.; HAFA has been used successfully to predict the structure of 18Sr RNA molecules from related organisms. This research has conclusively demonstrated that object-oriented techniques work effectively.; Traditional object-oriented design and analysis techniques are supplemented here to facilitate the design of class definitions and interrelationships, using a notationally extended context-sensitive grammar to derive and express data integrity constraints. Extensive testing and evaluation was performed to demonstrate the significance and accuracy of HAFA.