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Memory-efficient RNA energy landscape exploration
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; how...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4155248/ https://www.ncbi.nlm.nih.gov/pubmed/24833804 http://dx.doi.org/10.1093/bioinformatics/btu337 |
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author | Mann, Martin Kucharík, Marcel Flamm, Christoph Wolfinger, Michael T. |
author_facet | Mann, Martin Kucharík, Marcel Flamm, Christoph Wolfinger, Michael T. |
author_sort | Mann, Martin |
collection | PubMed |
description | 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/. Contact: mmann@informatik.uni-freiburg.de Supplementary information: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-4155248 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-41552482014-09-08 Memory-efficient RNA energy landscape exploration Mann, Martin Kucharík, Marcel Flamm, Christoph Wolfinger, Michael T. Bioinformatics Original Papers 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/. Contact: mmann@informatik.uni-freiburg.de Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2014-09-15 2014-05-14 /pmc/articles/PMC4155248/ /pubmed/24833804 http://dx.doi.org/10.1093/bioinformatics/btu337 Text en © The Author 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Papers Mann, Martin Kucharík, Marcel Flamm, Christoph Wolfinger, Michael T. Memory-efficient RNA energy landscape exploration |
title | Memory-efficient RNA energy landscape exploration |
title_full | Memory-efficient RNA energy landscape exploration |
title_fullStr | Memory-efficient RNA energy landscape exploration |
title_full_unstemmed | Memory-efficient RNA energy landscape exploration |
title_short | Memory-efficient RNA energy landscape exploration |
title_sort | memory-efficient rna energy landscape exploration |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4155248/ https://www.ncbi.nlm.nih.gov/pubmed/24833804 http://dx.doi.org/10.1093/bioinformatics/btu337 |
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