Title:  Can geometric combinatorics improve RNA folding prediction?
Abstract:  The formation of base pairs within single-stranded RNA molecules, such as viral genomes, creates structure and affects function. Yet, accurate prediction of this important folding information remains an open problem. The question is typically approached as a discrete optimization problem under a thermodynamic objective function. When reformulated as a linear program, we can fully analyze all possible multiloop entropy parameters using techniques from geometric combinatorics. In this way, we find new branching parameters which significantly increase prediction accuracy on well-defined families. Moreover, these results also illuminate why the general problem is so difficult.