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A comprehensive benchmark of RNA–RNA interaction prediction tools for all domains of life

MOTIVATION: The aim of this study is to assess the performance of RNA–RNA interaction prediction tools for all domains of life. RESULTS: Minimum free energy (MFE) and alignment methods constitute most of the current RNA interaction prediction algorithms. The MFE tools that include accessibility (i.e...

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Autores principales: Umu, Sinan Uğur, Gardner, Paul P
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408919/
https://www.ncbi.nlm.nih.gov/pubmed/27993777
http://dx.doi.org/10.1093/bioinformatics/btw728
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author Umu, Sinan Uğur
Gardner, Paul P
author_facet Umu, Sinan Uğur
Gardner, Paul P
author_sort Umu, Sinan Uğur
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description MOTIVATION: The aim of this study is to assess the performance of RNA–RNA interaction prediction tools for all domains of life. RESULTS: Minimum free energy (MFE) and alignment methods constitute most of the current RNA interaction prediction algorithms. The MFE tools that include accessibility (i.e. RNAup, IntaRNA and RNAplex) to the final predicted binding energy have better true positive rates (TPRs) with a high positive predictive values (PPVs) in all datasets than other methods. They can also differentiate almost half of the native interactions from background. The algorithms that include effects of internal binding energies to their model and alignment methods seem to have high TPR but relatively low associated PPV compared to accessibility based methods. AVAILABILITY AND IMPLEMENTATION: We shared our wrapper scripts and datasets at Github (github.com/UCanCompBio/RNA_Interactions_Benchmark). All parameters are documented for personal use. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-54089192017-05-03 A comprehensive benchmark of RNA–RNA interaction prediction tools for all domains of life Umu, Sinan Uğur Gardner, Paul P Bioinformatics Original Papers MOTIVATION: The aim of this study is to assess the performance of RNA–RNA interaction prediction tools for all domains of life. RESULTS: Minimum free energy (MFE) and alignment methods constitute most of the current RNA interaction prediction algorithms. The MFE tools that include accessibility (i.e. RNAup, IntaRNA and RNAplex) to the final predicted binding energy have better true positive rates (TPRs) with a high positive predictive values (PPVs) in all datasets than other methods. They can also differentiate almost half of the native interactions from background. The algorithms that include effects of internal binding energies to their model and alignment methods seem to have high TPR but relatively low associated PPV compared to accessibility based methods. AVAILABILITY AND IMPLEMENTATION: We shared our wrapper scripts and datasets at Github (github.com/UCanCompBio/RNA_Interactions_Benchmark). All parameters are documented for personal use. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2017-04-01 2016-12-30 /pmc/articles/PMC5408919/ /pubmed/27993777 http://dx.doi.org/10.1093/bioinformatics/btw728 Text en © The Author 2016. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Original Papers
Umu, Sinan Uğur
Gardner, Paul P
A comprehensive benchmark of RNA–RNA interaction prediction tools for all domains of life
title A comprehensive benchmark of RNA–RNA interaction prediction tools for all domains of life
title_full A comprehensive benchmark of RNA–RNA interaction prediction tools for all domains of life
title_fullStr A comprehensive benchmark of RNA–RNA interaction prediction tools for all domains of life
title_full_unstemmed A comprehensive benchmark of RNA–RNA interaction prediction tools for all domains of life
title_short A comprehensive benchmark of RNA–RNA interaction prediction tools for all domains of life
title_sort comprehensive benchmark of rna–rna interaction prediction tools for all domains of life
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408919/
https://www.ncbi.nlm.nih.gov/pubmed/27993777
http://dx.doi.org/10.1093/bioinformatics/btw728
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