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A novel method for high accuracy sumoylation site prediction from protein sequences
BACKGROUND: Protein sumoylation is an essential dynamic, reversible post translational modification that plays a role in dozens of cellular activities, especially the regulation of gene expression and the maintenance of genomic stability. Currently, the complexities of sumoylation mechanism can not...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2245905/ https://www.ncbi.nlm.nih.gov/pubmed/18179724 http://dx.doi.org/10.1186/1471-2105-9-8 |
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author | Xu, Jialin He, Yun Qiang, Boqin Yuan, Jiangang Peng, Xiaozhong Pan, Xian-Ming |
author_facet | Xu, Jialin He, Yun Qiang, Boqin Yuan, Jiangang Peng, Xiaozhong Pan, Xian-Ming |
author_sort | Xu, Jialin |
collection | PubMed |
description | BACKGROUND: Protein sumoylation is an essential dynamic, reversible post translational modification that plays a role in dozens of cellular activities, especially the regulation of gene expression and the maintenance of genomic stability. Currently, the complexities of sumoylation mechanism can not be perfectly solved by experimental approaches. In this regard, computational approaches might represent a promising method to direct experimental identification of sumoylation sites and shed light on the understanding of the reaction mechanism. RESULTS: Here we presented a statistical method for sumoylation site prediction. A 5-fold cross validation test over the experimentally identified sumoylation sites yielded excellent prediction performance with correlation coefficient, specificity, sensitivity and accuracy equal to 0.6364, 97.67%, 73.96% and 96.71% respectively. Additionally, the predictor performance is maintained when high level homologs are removed. CONCLUSION: By using a statistical method, we have developed a new SUMO site prediction method – SUMOpre, which has shown its great accuracy with correlation coefficient, specificity, sensitivity and accuracy. |
format | Text |
id | pubmed-2245905 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-22459052008-02-20 A novel method for high accuracy sumoylation site prediction from protein sequences Xu, Jialin He, Yun Qiang, Boqin Yuan, Jiangang Peng, Xiaozhong Pan, Xian-Ming BMC Bioinformatics Research Article BACKGROUND: Protein sumoylation is an essential dynamic, reversible post translational modification that plays a role in dozens of cellular activities, especially the regulation of gene expression and the maintenance of genomic stability. Currently, the complexities of sumoylation mechanism can not be perfectly solved by experimental approaches. In this regard, computational approaches might represent a promising method to direct experimental identification of sumoylation sites and shed light on the understanding of the reaction mechanism. RESULTS: Here we presented a statistical method for sumoylation site prediction. A 5-fold cross validation test over the experimentally identified sumoylation sites yielded excellent prediction performance with correlation coefficient, specificity, sensitivity and accuracy equal to 0.6364, 97.67%, 73.96% and 96.71% respectively. Additionally, the predictor performance is maintained when high level homologs are removed. CONCLUSION: By using a statistical method, we have developed a new SUMO site prediction method – SUMOpre, which has shown its great accuracy with correlation coefficient, specificity, sensitivity and accuracy. BioMed Central 2008-01-08 /pmc/articles/PMC2245905/ /pubmed/18179724 http://dx.doi.org/10.1186/1471-2105-9-8 Text en Copyright © 2008 Xu et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Xu, Jialin He, Yun Qiang, Boqin Yuan, Jiangang Peng, Xiaozhong Pan, Xian-Ming A novel method for high accuracy sumoylation site prediction from protein sequences |
title | A novel method for high accuracy sumoylation site prediction from protein sequences |
title_full | A novel method for high accuracy sumoylation site prediction from protein sequences |
title_fullStr | A novel method for high accuracy sumoylation site prediction from protein sequences |
title_full_unstemmed | A novel method for high accuracy sumoylation site prediction from protein sequences |
title_short | A novel method for high accuracy sumoylation site prediction from protein sequences |
title_sort | novel method for high accuracy sumoylation site prediction from protein sequences |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2245905/ https://www.ncbi.nlm.nih.gov/pubmed/18179724 http://dx.doi.org/10.1186/1471-2105-9-8 |
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