Memory efficient RNA energy landscape exploration
Abstract
Energy landscapes provide a valuable means for studying the folding dynamics of short RNA molecules in detail by modeling all possible structures and their transitions. Higher abstraction levels based on a macro-state decomposition of the landscape enable the study of larger systems, however they are still restricted by huge memory requirements of exact approaches. We present a highly parallelizable local enumeration scheme that enables the computation of exact macro-state transition models with highly reduced memory requirements. The approach is evaluated on RNA secondary structure landscapes using a gradient basin definition for macro-states. Furthermore, we demonstrate the need for exact transition models by comparing two barrier-based appoaches and perform a detailed investigation of gradient basins in RNA energy landscapes. Source code is part of the C++ Energy Landscape Library available at http://www.bioinf.uni-freiburg.de/Software/.
Keywords
Cite
@article{arxiv.1404.0270,
title = {Memory efficient RNA energy landscape exploration},
author = {Martin Mann and Marcel Kucharik and Christoph Flamm and Michael T. Wolfinger},
journal= {arXiv preprint arXiv:1404.0270},
year = {2014}
}