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GPS-SUMO: a tool for the prediction of sumoylation sites and SUMO-interaction motifs
Small ubiquitin-like modifiers (SUMOs) regulate a variety of cellular processes through two distinct mechanisms, including covalent sumoylation and non-covalent SUMO interaction. The complexity of SUMO regulations has greatly hampered the large-scale identification of SUMO substrates or interaction...
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/PMC4086084/ https://www.ncbi.nlm.nih.gov/pubmed/24880689 http://dx.doi.org/10.1093/nar/gku383 |
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author | Zhao, Qi Xie, Yubin Zheng, Yueyuan Jiang, Shuai Liu, Wenzhong Mu, Weiping Liu, Zexian Zhao, Yong Xue, Yu Ren, Jian |
author_facet | Zhao, Qi Xie, Yubin Zheng, Yueyuan Jiang, Shuai Liu, Wenzhong Mu, Weiping Liu, Zexian Zhao, Yong Xue, Yu Ren, Jian |
author_sort | Zhao, Qi |
collection | PubMed |
description | Small ubiquitin-like modifiers (SUMOs) regulate a variety of cellular processes through two distinct mechanisms, including covalent sumoylation and non-covalent SUMO interaction. The complexity of SUMO regulations has greatly hampered the large-scale identification of SUMO substrates or interaction partners on a proteome-wide level. In this work, we developed a new tool called GPS-SUMO for the prediction of both sumoylation sites and SUMO-interaction motifs (SIMs) in proteins. To obtain an accurate performance, a new generation group-based prediction system (GPS) algorithm integrated with Particle Swarm Optimization approach was applied. By critical evaluation and comparison, GPS-SUMO was demonstrated to be substantially superior against other existing tools and methods. With the help of GPS-SUMO, it is now possible to further investigate the relationship between sumoylation and SUMO interaction processes. A web service of GPS-SUMO was implemented in PHP + JavaScript and freely available at http://sumosp.biocuckoo.org. |
format | Online Article Text |
id | pubmed-4086084 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-40860842014-12-01 GPS-SUMO: a tool for the prediction of sumoylation sites and SUMO-interaction motifs Zhao, Qi Xie, Yubin Zheng, Yueyuan Jiang, Shuai Liu, Wenzhong Mu, Weiping Liu, Zexian Zhao, Yong Xue, Yu Ren, Jian Nucleic Acids Res Article Small ubiquitin-like modifiers (SUMOs) regulate a variety of cellular processes through two distinct mechanisms, including covalent sumoylation and non-covalent SUMO interaction. The complexity of SUMO regulations has greatly hampered the large-scale identification of SUMO substrates or interaction partners on a proteome-wide level. In this work, we developed a new tool called GPS-SUMO for the prediction of both sumoylation sites and SUMO-interaction motifs (SIMs) in proteins. To obtain an accurate performance, a new generation group-based prediction system (GPS) algorithm integrated with Particle Swarm Optimization approach was applied. By critical evaluation and comparison, GPS-SUMO was demonstrated to be substantially superior against other existing tools and methods. With the help of GPS-SUMO, it is now possible to further investigate the relationship between sumoylation and SUMO interaction processes. A web service of GPS-SUMO was implemented in PHP + JavaScript and freely available at http://sumosp.biocuckoo.org. Oxford University Press 2014-07-01 2014-05-31 /pmc/articles/PMC4086084/ /pubmed/24880689 http://dx.doi.org/10.1093/nar/gku383 Text en © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research. 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 | Article Zhao, Qi Xie, Yubin Zheng, Yueyuan Jiang, Shuai Liu, Wenzhong Mu, Weiping Liu, Zexian Zhao, Yong Xue, Yu Ren, Jian GPS-SUMO: a tool for the prediction of sumoylation sites and SUMO-interaction motifs |
title | GPS-SUMO: a tool for the prediction of sumoylation sites and SUMO-interaction motifs |
title_full | GPS-SUMO: a tool for the prediction of sumoylation sites and SUMO-interaction motifs |
title_fullStr | GPS-SUMO: a tool for the prediction of sumoylation sites and SUMO-interaction motifs |
title_full_unstemmed | GPS-SUMO: a tool for the prediction of sumoylation sites and SUMO-interaction motifs |
title_short | GPS-SUMO: a tool for the prediction of sumoylation sites and SUMO-interaction motifs |
title_sort | gps-sumo: a tool for the prediction of sumoylation sites and sumo-interaction motifs |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086084/ https://www.ncbi.nlm.nih.gov/pubmed/24880689 http://dx.doi.org/10.1093/nar/gku383 |
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