@article{Mann_basin_14,
  author = 	 {Martin Mann and Marcel Kucharik and Christoph Flamm and Michael T. Wolfinger},
  title = 	 {Memory efficient {RNA} energy landscape exploration},
  journal= 	 {Bioinformatics},
  year = 	 {2014},
  pages = 	 {2584-2591},
  volume = 	 {30},
  number = 	 {18},
  arxiv= 	 {1404.0270},
  doi = 	 {10.1093/bioinformatics/btu337},
  pmid = 	 {24833804},
  issn = 	 {1367-4811},
  issn = 	 {1367-4803},
  user = 	 {mmann},
  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/.}
}