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A statistical analysis of RNA folding algorithms through thermodynamic parameter perturbation

Computational RNA secondary structure prediction is rather well established. However, such prediction algorithms always depend on a large number of experimentally measured parameters. Here, we study how sensitive structure prediction algorithms are to changes in these parameters. We found already th...

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Detalles Bibliográficos
Autores principales: Layton, D. M., Bundschuh, R.
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC548333/
https://www.ncbi.nlm.nih.gov/pubmed/15673712
http://dx.doi.org/10.1093/nar/gkh983
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author Layton, D. M.
Bundschuh, R.
author_facet Layton, D. M.
Bundschuh, R.
author_sort Layton, D. M.
collection PubMed
description Computational RNA secondary structure prediction is rather well established. However, such prediction algorithms always depend on a large number of experimentally measured parameters. Here, we study how sensitive structure prediction algorithms are to changes in these parameters. We found already that for changes corresponding to the actual experimental error to which these parameters have been determined, 30% of the structure are falsely predicted whereas the ground state structure is preserved under parameter perturbation in only 5% of all the cases. We establish that base-pairing probabilities calculated in a thermal ensemble are viable although not a perfect measure for the reliability of the prediction of individual structure elements. Here, a new measure of stability using parameter perturbation is proposed, and its limitations are discussed.
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spelling pubmed-5483332005-02-10 A statistical analysis of RNA folding algorithms through thermodynamic parameter perturbation Layton, D. M. Bundschuh, R. Nucleic Acids Res Article Computational RNA secondary structure prediction is rather well established. However, such prediction algorithms always depend on a large number of experimentally measured parameters. Here, we study how sensitive structure prediction algorithms are to changes in these parameters. We found already that for changes corresponding to the actual experimental error to which these parameters have been determined, 30% of the structure are falsely predicted whereas the ground state structure is preserved under parameter perturbation in only 5% of all the cases. We establish that base-pairing probabilities calculated in a thermal ensemble are viable although not a perfect measure for the reliability of the prediction of individual structure elements. Here, a new measure of stability using parameter perturbation is proposed, and its limitations are discussed. Oxford University Press 2005 2005-01-26 /pmc/articles/PMC548333/ /pubmed/15673712 http://dx.doi.org/10.1093/nar/gkh983 Text en © The Author 2005. Published by Oxford University Press. All rights reserved
spellingShingle Article
Layton, D. M.
Bundschuh, R.
A statistical analysis of RNA folding algorithms through thermodynamic parameter perturbation
title A statistical analysis of RNA folding algorithms through thermodynamic parameter perturbation
title_full A statistical analysis of RNA folding algorithms through thermodynamic parameter perturbation
title_fullStr A statistical analysis of RNA folding algorithms through thermodynamic parameter perturbation
title_full_unstemmed A statistical analysis of RNA folding algorithms through thermodynamic parameter perturbation
title_short A statistical analysis of RNA folding algorithms through thermodynamic parameter perturbation
title_sort statistical analysis of rna folding algorithms through thermodynamic parameter perturbation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC548333/
https://www.ncbi.nlm.nih.gov/pubmed/15673712
http://dx.doi.org/10.1093/nar/gkh983
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