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IRSOM2: a web server for predicting bifunctional RNAs
Recent advances have shown that some biologically active non-coding RNAs (ncRNAs) are actually translated into polypeptides that have a physiological function as well. This paradigm shift requires adapted computational methods to predict this new class of ‘bifunctional RNAs’. Previously, we develope...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10320184/ https://www.ncbi.nlm.nih.gov/pubmed/37158254 http://dx.doi.org/10.1093/nar/gkad381 |
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author | Postic, Guillaume Tav, Christophe Platon, Ludovic Zehraoui, Farida Tahi, Fariza |
author_facet | Postic, Guillaume Tav, Christophe Platon, Ludovic Zehraoui, Farida Tahi, Fariza |
author_sort | Postic, Guillaume |
collection | PubMed |
description | Recent advances have shown that some biologically active non-coding RNAs (ncRNAs) are actually translated into polypeptides that have a physiological function as well. This paradigm shift requires adapted computational methods to predict this new class of ‘bifunctional RNAs’. Previously, we developed IRSOM, an open-source algorithm to classify non-coding and coding RNAs. Here, we use the binary statistical model of IRSOM as a ternary classifier, called IRSOM2, to identify bifunctional RNAs as a rejection of the two other classes. We present its easy-to-use web interface, which allows users to perform predictions on large datasets of RNA sequences in a short time, to re-train the model with their own data, and to visualize and analyze the classification results thanks to the implementation of self-organizing maps (SOM). We also propose a new benchmark of experimentally validated RNAs that play both protein-coding and non-coding roles, in different organisms. Thus, IRSOM2 showed promising performance in detecting these bifunctional transcripts among ncRNAs of different types, such as circRNAs and lncRNAs (in particular those of shorter lengths). The web server is freely available on the EvryRNA platform: https://evryrna.ibisc.univ-evry.fr. |
format | Online Article Text |
id | pubmed-10320184 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-103201842023-07-06 IRSOM2: a web server for predicting bifunctional RNAs Postic, Guillaume Tav, Christophe Platon, Ludovic Zehraoui, Farida Tahi, Fariza Nucleic Acids Res Web Server Issue Recent advances have shown that some biologically active non-coding RNAs (ncRNAs) are actually translated into polypeptides that have a physiological function as well. This paradigm shift requires adapted computational methods to predict this new class of ‘bifunctional RNAs’. Previously, we developed IRSOM, an open-source algorithm to classify non-coding and coding RNAs. Here, we use the binary statistical model of IRSOM as a ternary classifier, called IRSOM2, to identify bifunctional RNAs as a rejection of the two other classes. We present its easy-to-use web interface, which allows users to perform predictions on large datasets of RNA sequences in a short time, to re-train the model with their own data, and to visualize and analyze the classification results thanks to the implementation of self-organizing maps (SOM). We also propose a new benchmark of experimentally validated RNAs that play both protein-coding and non-coding roles, in different organisms. Thus, IRSOM2 showed promising performance in detecting these bifunctional transcripts among ncRNAs of different types, such as circRNAs and lncRNAs (in particular those of shorter lengths). The web server is freely available on the EvryRNA platform: https://evryrna.ibisc.univ-evry.fr. Oxford University Press 2023-05-09 /pmc/articles/PMC10320184/ /pubmed/37158254 http://dx.doi.org/10.1093/nar/gkad381 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://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 | Web Server Issue Postic, Guillaume Tav, Christophe Platon, Ludovic Zehraoui, Farida Tahi, Fariza IRSOM2: a web server for predicting bifunctional RNAs |
title | IRSOM2: a web server for predicting bifunctional RNAs |
title_full | IRSOM2: a web server for predicting bifunctional RNAs |
title_fullStr | IRSOM2: a web server for predicting bifunctional RNAs |
title_full_unstemmed | IRSOM2: a web server for predicting bifunctional RNAs |
title_short | IRSOM2: a web server for predicting bifunctional RNAs |
title_sort | irsom2: a web server for predicting bifunctional rnas |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10320184/ https://www.ncbi.nlm.nih.gov/pubmed/37158254 http://dx.doi.org/10.1093/nar/gkad381 |
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