Lachtermann Lecture: Can geometric combinatorics improve RNA folding predictions?
Abstract: Understanding the folding of RNA sequences into three-dimensional structures, such as a viral genome inside its protein capsid, is a fundamental scientific challenge. Branching is a critical characteristic of RNA folding, yet too often poorly predicted under standard thermodynamic optimization methods. By formulating this discrete optimization problem as a linear program, we can fully characterize how predictions depend on the branching model parameters using geometric combinatorics. Through this parametric analysis of the associated convex polytopes and their normal fans, we can significantly improve RNA branching prediction accuracy on well-defined families while also illuminating why the general problem is so difficult.
Host: Brett Wick
Before the colloquium, there will be tea served in Room 200 (Lounge) at 3:30.