Ribonucleic acid (RNA) molecules play important roles in many biological processes including gene expression and regulation. An RNA molecule is a linear polymer which folds back on itself to form a three dimensional (3D) functional structure. While experimental determination of precise 3D RNA structures is a time consuming and costly process, useful insight into the molecule can be gained from knowing its secondary structure. Structural elements in RNA secondary structures can be separated into two large categories: stem-loops and pseudoknots. The development of mathematical models and computational prediction algorithms for simple stem-loop structures started early in the 1980’s. However, building systems that provide the tremendous computer time and memory needed for RNA analysis of both stem-loops and pseudoknots remains a challenge even today. The recently developed grid computing technology can offer a possible solution to this challenge. In this paper we briefly address mathem...
Michela Taufer, Ming-Ying Leung, Kyle L. Johnson,