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Bioinformatics Group, Department of Computer Science, University of Freiburg, 79110 Freiburg, Germany, Institute for Theoretical Chemistry, University of Vienna, 1090 Vienna, Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, and Department of Biochemistry and Molecular Cell Biology, Max F. Perutz Laboratories, University of Vienna, A-1030 Vienna, Austria Bioinformatics Group, Department of Computer Science, University of Freiburg, 79110 Freiburg, Germany, Institute for Theoretical Chemistry, University of Vienna, 1090 Vienna, Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, and Department of Biochemistry and Molecular Cell Biology, Max F. Perutz Laboratories, University of Vienna, A-1030 Vienna, Austria Bioinformatics Group, Department of Computer Science, University of Freiburg, 79110 Freiburg, Germany, Institute for Theoretical Chemistry, University of Vienna, 1090 Vienna, Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, and Department of Biochemistry and Molecular Cell Biology, Max F. Perutz Laboratories, University of Vienna, A-1030 Vienna, Austria.
Published: September 2014
AI Article Synopsis
Article Abstract
Motivation: 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.
Results: 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 approaches, and perform a detailed investigation of gradient basins in RNA energy landscapes.
Availability And Implementation: Source code is part of the C++ Energy Landscape Library available at http://www.bioinf.uni-freiburg.de/Software/.
