TBI-p-2014-7
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Titel:
Memory efficient RNA energy landscape exploration
Author(s):
Martin Mann, Marcel Kucharík, Christoph Flamm and Michael T. Wolfinger
submitted to:
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 appoaches and perform a detailed investigation of gradient basins in
RNA energy landscapes.
Availability: Source code is part of the C++ Energy Landscape
Library available at http://www.bioinf.uni-freiburg.de/Software/.
Contact: mmann@informatik.uni-freiburg.de
Link to publication:
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Last modified: 2008-10-22 12:23:11 fall