Conditioning and Robustness of RNA Boltzmann Sampling under Thermodynamic Parameter Perturbations.

ABSTRACT: Understanding how RNA secondary structure prediction methods depend on the underlying nearest-neighbor thermodynamic model remains a fundamental challenge in the field. Minimum free energy (MFE) predictions are known to be "ill conditioned" in that small changes to the thermodynamic model can result in significantly different optimal structures. Hence, the best practice is now to sample from the Boltzmann distribution, which generates a set of suboptimal structures. Although the structural signal of this Boltzmann sample is known to be robust to stochastic noise, the conditioning and robustness under thermodynamic perturbations have yet to be addressed. We present here a mathematically rigorous model for conditioning inspired by numerical analysis, and also a biologically inspired definiti

SUBMITTER: Rogers E 

PROVIDER: S-EPMC5529178 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature