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PCPPI: a comprehensive database for the prediction of Penicillium–crop protein–protein interactions
Penicillium expansum, the causal agent of blue mold, is one of the most prevalent post-harvest pathogens, infecting a wide range of crops after harvest. In response, crops have evolved various defense systems to protect themselves against this and other pathogens. Penicillium–crop interaction is a m...
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/PMC5467543/ https://www.ncbi.nlm.nih.gov/pubmed/28365721 http://dx.doi.org/10.1093/database/baw170 |
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author | Yue, Junyang Zhang, Danfeng Ban, Rongjun Ma, Xiaojing Chen, Danyang Li, Guangwei Liu, Jia Wisniewski, Michael Droby, Samir Liu, Yongsheng |
author_facet | Yue, Junyang Zhang, Danfeng Ban, Rongjun Ma, Xiaojing Chen, Danyang Li, Guangwei Liu, Jia Wisniewski, Michael Droby, Samir Liu, Yongsheng |
author_sort | Yue, Junyang |
collection | PubMed |
description | Penicillium expansum, the causal agent of blue mold, is one of the most prevalent post-harvest pathogens, infecting a wide range of crops after harvest. In response, crops have evolved various defense systems to protect themselves against this and other pathogens. Penicillium–crop interaction is a multifaceted process and mediated by pathogen- and host-derived proteins. Identification and characterization of the inter-species protein–protein interactions (PPIs) are fundamental to elucidating the molecular mechanisms underlying infection processes between P. expansum and plant crops. Here, we have developed PCPPI, the Penicillium-Crop Protein–Protein Interactions database, which is constructed based on the experimentally determined orthologous interactions in pathogen–plant systems and available domain–domain interactions (DDIs) in each PPI. Thus far, it stores information on 9911 proteins, 439 904 interactions and seven host species, including apple, kiwifruit, maize, pear, rice, strawberry and tomato. Further analysis through the gene ontology (GO) annotation indicated that proteins with more interacting partners tend to execute the essential function. Significantly, semantic statistics of the GO terms also provided strong support for the accuracy of our predicted interactions in PCPPI. We believe that all the PCPPI datasets are helpful to facilitate the study of pathogen-crop interactions and freely available to the research community. Database URL: http://bdg.hfut.edu.cn/pcppi/index.html |
format | Online Article Text |
id | pubmed-5467543 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-54675432017-06-19 PCPPI: a comprehensive database for the prediction of Penicillium–crop protein–protein interactions Yue, Junyang Zhang, Danfeng Ban, Rongjun Ma, Xiaojing Chen, Danyang Li, Guangwei Liu, Jia Wisniewski, Michael Droby, Samir Liu, Yongsheng Database (Oxford) Database Tool Penicillium expansum, the causal agent of blue mold, is one of the most prevalent post-harvest pathogens, infecting a wide range of crops after harvest. In response, crops have evolved various defense systems to protect themselves against this and other pathogens. Penicillium–crop interaction is a multifaceted process and mediated by pathogen- and host-derived proteins. Identification and characterization of the inter-species protein–protein interactions (PPIs) are fundamental to elucidating the molecular mechanisms underlying infection processes between P. expansum and plant crops. Here, we have developed PCPPI, the Penicillium-Crop Protein–Protein Interactions database, which is constructed based on the experimentally determined orthologous interactions in pathogen–plant systems and available domain–domain interactions (DDIs) in each PPI. Thus far, it stores information on 9911 proteins, 439 904 interactions and seven host species, including apple, kiwifruit, maize, pear, rice, strawberry and tomato. Further analysis through the gene ontology (GO) annotation indicated that proteins with more interacting partners tend to execute the essential function. Significantly, semantic statistics of the GO terms also provided strong support for the accuracy of our predicted interactions in PCPPI. We believe that all the PCPPI datasets are helpful to facilitate the study of pathogen-crop interactions and freely available to the research community. Database URL: http://bdg.hfut.edu.cn/pcppi/index.html Oxford University Press 2017-02-26 /pmc/articles/PMC5467543/ /pubmed/28365721 http://dx.doi.org/10.1093/database/baw170 Text en © The Author(s) 2017. 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 | Database Tool Yue, Junyang Zhang, Danfeng Ban, Rongjun Ma, Xiaojing Chen, Danyang Li, Guangwei Liu, Jia Wisniewski, Michael Droby, Samir Liu, Yongsheng PCPPI: a comprehensive database for the prediction of Penicillium–crop protein–protein interactions |
title | PCPPI: a comprehensive database for the prediction of Penicillium–crop protein–protein interactions |
title_full | PCPPI: a comprehensive database for the prediction of Penicillium–crop protein–protein interactions |
title_fullStr | PCPPI: a comprehensive database for the prediction of Penicillium–crop protein–protein interactions |
title_full_unstemmed | PCPPI: a comprehensive database for the prediction of Penicillium–crop protein–protein interactions |
title_short | PCPPI: a comprehensive database for the prediction of Penicillium–crop protein–protein interactions |
title_sort | pcppi: a comprehensive database for the prediction of penicillium–crop protein–protein interactions |
topic | Database Tool |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5467543/ https://www.ncbi.nlm.nih.gov/pubmed/28365721 http://dx.doi.org/10.1093/database/baw170 |
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