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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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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 |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-5408919 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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