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BEAN 2.0: an integrated web resource for the identification and functional analysis of type III secreted effectors
Gram-negative pathogenic bacteria inject type III secreted effectors (T3SEs) into host cells to sabotage their immune signaling networks. Because T3SEs constitute a meeting-point of pathogen virulence and host defense, they are of keen interest to host–pathogen interaction research community. To acc...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4483310/ https://www.ncbi.nlm.nih.gov/pubmed/26120140 http://dx.doi.org/10.1093/database/bav064 |
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author | Dong, Xiaobao Lu, Xiaotian Zhang, Ziding |
author_facet | Dong, Xiaobao Lu, Xiaotian Zhang, Ziding |
author_sort | Dong, Xiaobao |
collection | PubMed |
description | Gram-negative pathogenic bacteria inject type III secreted effectors (T3SEs) into host cells to sabotage their immune signaling networks. Because T3SEs constitute a meeting-point of pathogen virulence and host defense, they are of keen interest to host–pathogen interaction research community. To accelerate the identification and functional understanding of T3SEs, we present BEAN 2.0 as an integrated web resource to predict, analyse and store T3SEs. BEAN 2.0 includes three major components. First, it provides an accurate T3SE predictor based on a hybrid approach. Using independent testing data, we show that BEAN 2.0 achieves a sensitivity of 86.05% and a specificity of 100%. Second, it integrates a set of online sequence analysis tools. Users can further perform functional analysis of putative T3SEs in a seamless way, such as subcellular location prediction, functional domain scan and disorder region annotation. Third, it compiles a database covering 1215 experimentally verified T3SEs and constructs two T3SE-related networks that can be used to explore the relationships among T3SEs. Taken together, by presenting a one-stop T3SE bioinformatics resource, we hope BEAN 2.0 can promote comprehensive understanding of the function and evolution of T3SEs. Database URL: http://systbio.cau.edu.cn/bean/ |
format | Online Article Text |
id | pubmed-4483310 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-44833102015-06-30 BEAN 2.0: an integrated web resource for the identification and functional analysis of type III secreted effectors Dong, Xiaobao Lu, Xiaotian Zhang, Ziding Database (Oxford) Original Article Gram-negative pathogenic bacteria inject type III secreted effectors (T3SEs) into host cells to sabotage their immune signaling networks. Because T3SEs constitute a meeting-point of pathogen virulence and host defense, they are of keen interest to host–pathogen interaction research community. To accelerate the identification and functional understanding of T3SEs, we present BEAN 2.0 as an integrated web resource to predict, analyse and store T3SEs. BEAN 2.0 includes three major components. First, it provides an accurate T3SE predictor based on a hybrid approach. Using independent testing data, we show that BEAN 2.0 achieves a sensitivity of 86.05% and a specificity of 100%. Second, it integrates a set of online sequence analysis tools. Users can further perform functional analysis of putative T3SEs in a seamless way, such as subcellular location prediction, functional domain scan and disorder region annotation. Third, it compiles a database covering 1215 experimentally verified T3SEs and constructs two T3SE-related networks that can be used to explore the relationships among T3SEs. Taken together, by presenting a one-stop T3SE bioinformatics resource, we hope BEAN 2.0 can promote comprehensive understanding of the function and evolution of T3SEs. Database URL: http://systbio.cau.edu.cn/bean/ Oxford University Press 2015-06-27 /pmc/articles/PMC4483310/ /pubmed/26120140 http://dx.doi.org/10.1093/database/bav064 Text en © The Author(s) 2015. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Dong, Xiaobao Lu, Xiaotian Zhang, Ziding BEAN 2.0: an integrated web resource for the identification and functional analysis of type III secreted effectors |
title | BEAN 2.0: an integrated web resource for the identification and functional analysis of type III secreted effectors |
title_full | BEAN 2.0: an integrated web resource for the identification and functional analysis of type III secreted effectors |
title_fullStr | BEAN 2.0: an integrated web resource for the identification and functional analysis of type III secreted effectors |
title_full_unstemmed | BEAN 2.0: an integrated web resource for the identification and functional analysis of type III secreted effectors |
title_short | BEAN 2.0: an integrated web resource for the identification and functional analysis of type III secreted effectors |
title_sort | bean 2.0: an integrated web resource for the identification and functional analysis of type iii secreted effectors |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4483310/ https://www.ncbi.nlm.nih.gov/pubmed/26120140 http://dx.doi.org/10.1093/database/bav064 |
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